JP2023019126A - Vehicle traveling managing system - Google Patents

Abstract

To decrease a possibility that both vehicles collide with each other by controlling the operation of an unmanned traveling vehicle in an environment in which a manned traveling vehicle and the unmanned traveling vehicle coexist and travel.SOLUTION: The manned traveling vehicle estimates information on an own present position and an advancing direction from map information, a cumulative movement amount including a moving distance from an initial position and an angular change amount calculated by using a measured rotation speed of wheels and a measured steering turn angle, distance measurement information to an obstacle, and information on a position of the obstacle. The unmanned vehicle estimates information on an own present position and an advancing direction from map information, a cumulative movement amount including a movement distance from an initial position and an angular change amount calculated by using a measured rotation speed of wheels. Whether or not both the vehicles are coming close to each other is determined by using the information on the respective present positions and the respective advancing directions obtained from the unmanned traveling vehicle and the manned traveling vehicle.SELECTED DRAWING: Figure 14

Description

The present invention relates to a vehicle running management system, and more particularly to a vehicle running management system that manages the running of manned and unmanned vehicles used in factories, warehouses, etc., capable of transporting cargo.

BACKGROUND ART Today, in buildings such as factories and warehouses, manned guided vehicles such as forklifts driven by humans and unmanned guided vehicles that operate automatically without human operation are used to transport packages.
An automated guided vehicle (hereinafter also referred to as an AGV) receives an instruction signal from a travel management device, travels to a predetermined point, and picks up and transports cargo.

Electromagnetic induction, magnetic induction, image recognition, etc. are used as methods for guiding an automated guided vehicle (AGV) to a predetermined point.
In the electromagnetic induction system, a weak alternating current is passed through metal wires installed on the floor, and the generated magnetic field is detected by the coils mounted on the AGV, and the AGV is driven along a predetermined route.
In the magnetic induction system, a magnetic tape is embedded in the floor, and a magnetic sensor mounted on the AGV reads the magnetic tape, and the AGV runs along a predetermined route.
In the image recognition method, a camera mounted on the AGV reads predetermined position marks and two-dimensional codes placed on the floor, etc., and drives the AGV along a predetermined route while recognizing the vehicle's position.

For example, in Patent Document 1, in a situation where manned and unmanned forklifts, which are cargo handling vehicles, coexist, guide lines and position marks are provided on the road surface of the travel route of the forklift to guide the movement of the forklift. The guidance lines and position marks are photographed by the installed camera, the position information of the forklift detected from the position marks included in the photographed image is transmitted to the management device, and the management device identifies the current position of each forklift. , the travel route of the manned forklift and the travel route of the unmanned forklift are identified, and if the travel position of the manned forklift and the travel position of the unmanned forklift will be within a predetermined distance at the same time in the future A cargo handling vehicle system is described in which, when determined, an instruction to evacuate an unmanned forklift to a route branched from a travel route is transmitted from a management device to the unmanned forklift.

Also, using SLAM (Simultaneous Localization and Mapping) technology based on LiDAR (Lidar: Laser Imaging Detection and Ranging), autonomous guided vehicles (AGV) that estimate where they are on the map are also used. It is

When such an automatic guided vehicle (AGV) is used for collection work or the like in a warehouse, the AGV travels between product shelves for shipping according to a transport instruction from the management device, and performs the shipping work or the like.
In addition, the management device calculates the inventory amount of the merchandise on the merchandise shelf from the operation status of the AGV, and instructs the person in charge of operation to replenish the merchandise before the inventory amount runs short.
Thereafter, for example, the worker carries the pallet loaded with the products by a manned forklift or the like, and stores the products on the product shelves for shipping, thereby replenishing the products. Forklifts for replenishment of this product are often not self-driving but manned forklifts (manned guided vehicles) driven by workers.
In such warehouses, a large number of automated guided vehicles (AGV) travel along predetermined routes between product shelves in accordance with transport instructions for the work of unloading each product, and a large number of manned forklifts are also installed. moves within the warehouse to deliver replenishment products.

JP 2018-60317 A

However, in general, manned forklifts (manned guided vehicles) have higher running performance and can move faster than automated guided vehicles (AGVs).
In addition, since the driver's seat of manned forklifts is in a standing position or the seating position of the driver's seat is high, there is a risk that the driver may overlook the AGV, which is relatively low.
Therefore, if the driver of the forklift moving at high speed overlooks the autonomously traveling AGV, the manned forklift may collide with the AGV.

In addition, although AGVs have a function of detecting obstacles, they may travel in places that deviate from prescribed routes in order to avoid obstacles during autonomous travel.
Unlike the case where the driver pushes the truck, the AGV does not allow non-verbal communication such as eye contact between humans.
As a result, there is a risk of accidents such as manned forklifts colliding with AGVs or other obstacles.

In addition, the LiDAR attached to the AGV emits laser light radially and measures the distance to the obstacle to detect the position of the obstacle.
In the case of a stationary obstacle, the AGV can avoid the obstacle with relative ease. It is necessary to detect obstacles and take actions to avoid collisions.
However, the information acquired by LiDAR cannot recognize that the detected obstacle is a forklift, so it is difficult to judge whether the obstacle is approaching at high speed. Collision avoidance may not be possible with only the acquired information.

Therefore, the present invention has been made in consideration of the circumstances as described above. To provide a vehicle travel management system capable of reducing the possibility of collision between a manned vehicle and an unmanned vehicle by controlling the operation of the unmanned vehicle from the current position and orientation of the vehicle.

The present invention relates to a vehicle travel management system in which a manned vehicle and an unmanned vehicle capable of autonomous travel are connected via a network, wherein the unmanned vehicle operates in a pre-stored spatial region in which it travels. Map information, the distance traveled from the initial position calculated using the measured number of rotations of the wheels, the amount of angular change from the initial position at the initial position, and the cumulative amount of movement, and the distance to the obstacle. Information about the current position and traveling direction of the vehicle on the map of the spatial area is estimated using the ranging information, and the manned vehicle uses the map information of the spatial area used by the unmanned vehicle and the measured information. The accumulated movement amount consisting of the distance moved from the starting initial position calculated using the number of rotations of the wheel and the rotation angle of the steering wheel and the amount of change in angle from the initial orientation at the initial position, and the distance to the obstacle. using the ranging information to estimate information about its own current position and traveling direction on the map of the spatial area, and the unmanned vehicle receives information about the estimated current position and traveling direction of the unmanned traveling vehicle; determining whether or not the unmanned vehicle and the manned vehicle are approaching using the estimated current position and traveling direction information of the manned vehicle; A vehicle running management system characterized by controlling the operation of a running vehicle is provided.

The present invention also provides a travel management method for a vehicle travel management system in which a manned vehicle and an unmanned vehicle capable of autonomous travel are connected via a network, wherein the unmanned vehicle is stored in advance. The distance traveled from the initial position when the unmanned vehicle was started and the angular change from the initial orientation at the initial position calculated using the map information of the space area in which the vehicle travels, and the number of rotations of the wheels measured by the encoder. A first self-position estimating step of estimating information about the current position and traveling direction of the self on the map of the spatial area from the first accumulated movement amount consisting of the amount and information about the position of the obstacle existing in the traveling direction. Then, the manned traveling vehicle, which is calculated using the map information of the spatial area used by the unmanned traveling vehicle, the number of rotations of the wheel and the rotation angle of the steering wheel measured by the encoder, is started. Based on the second cumulative movement amount consisting of the distance moved from the initial position and the angular change amount from the initial bearing at the initial position, and the information on the position of the obstacle existing in the direction of travel, the self position on the map of the spatial area is obtained. a second self-position estimation step of estimating information about the current position and traveling direction; a first vehicle approach determination step of determining whether or not an unmanned vehicle and a manned vehicle are approaching using information; Unmanned vehicle operation control for controlling the operation of the unmanned vehicle so that the unmanned vehicle and the manned vehicle do not collide when it is determined that the vehicle and the manned vehicle are approaching within a predetermined distance. A running management method for a vehicle running management system, comprising:

According to the present invention, the manned vehicle uses the accumulated amount of movement, which is the distance moved from the initial position and the amount of angular change from the initial orientation at the initial position, to determine the current position of the vehicle on the map of the spatial area. and information about the direction of travel, and the unmanned vehicle uses the accumulated amount of movement, which is the distance traveled from the initial position and the amount of angular change from the initial orientation at the initial position, to estimate the self on the map of the spatial domain. information on the current position and direction of travel of the unmanned vehicle, and the information on the current position and direction of travel of the manned vehicle estimated on the map of the same spatial area, and the information on the current position and direction of travel of the unmanned vehicle This information is used to determine whether or not a manned vehicle and an unmanned vehicle are approaching, and to control the operation of the unmanned vehicle, so the possibility of a collision between the manned vehicle and the unmanned vehicle is prevented. can be reduced.
Also, for both the manned vehicle and the unmanned vehicle, the cumulative movement amount is calculated from the distance moved from the initial position and the angular change amount from the initial orientation at the initial position. Information on the current position and direction of travel on the map of the same spatial area is estimated using distance measurement information to obstacles existing in the space area. Since the estimation can be made with higher accuracy and the accuracy of the current position is high, it is possible to safely control the traveling of both vehicles in a space area where manned vehicles and unmanned vehicles coexist.

1 is a schematic configuration diagram of a vehicle running management system of the present invention; FIG. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is an explanatory diagram of a functional configuration of one embodiment of a travel management device of the present invention; 1 is an explanatory diagram of a functional configuration of an embodiment of a manned guided vehicle according to the present invention; FIG. 1 is an explanatory diagram of a functional configuration of an embodiment of an automatic guided vehicle according to the present invention; FIG. 1 is an explanatory diagram of an embodiment of a region where manned and unmanned guided vehicles of the present invention travel; FIG. 1 is a schematic perspective view of one embodiment of a manned vehicle (forklift) of the present invention; FIG. 1 is a schematic perspective view of one embodiment of a manned vehicle (forklift) of the present invention; FIG. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a schematic configuration layout diagram of an embodiment of a manned guided vehicle (forklift) of the present invention viewed from above; BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a schematic configuration layout diagram of an embodiment of a manned guided vehicle (forklift) of the present invention viewed from above; BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a schematic configuration layout diagram of an embodiment of an automatic guided vehicle (AGV) of the present invention viewed from above; BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a schematic configuration layout diagram of an embodiment viewed from the side of an automatic guided vehicle (AGV) of the present invention; 4 is a flowchart of an embodiment of vehicle approach determination and travel control processing in the travel management system of the present invention; 4 is a flowchart of an embodiment of vehicle approach determination and travel control processing in the automatic guided vehicle of the present invention; 1 is a configuration block diagram of an embodiment related to self-position estimation processing of a manned guided vehicle (forklift) according to the present invention; FIG. 1 is a configuration block diagram of an embodiment related to self-position estimation processing of an automatic guided vehicle AGV of the present invention; FIG. FIG. 4 is a configuration block diagram of an embodiment related to obstacle information generation processing of the automatic guided vehicle AGV of the present invention; FIG. 4 is a configuration block diagram of an embodiment related to obstacle information generation processing of the automatic guided vehicle AGV of the present invention; FIG. 4 is an explanatory diagram of one embodiment of MV position information stored in the storage unit of the automatic guided vehicle AGV of the present invention; FIG. 4 is an explanatory diagram of one embodiment of MV shape information stored in the storage unit of the automatic guided vehicle AGV of the present invention; FIG. 4 is an explanatory diagram of an example of map coordinates obtained by superimposing MV position information and MV shape information; FIG. 4 is an explanatory diagram of one embodiment of MV point group information stored in the storage unit of the automatic guided vehicle AGV of the present invention; FIG. 4 is an explanatory diagram of an embodiment of the LiDAR measurement range of the automatic guided vehicle AGV and AGV ranging information of the present invention; FIG. 4 is an explanatory diagram of one embodiment of AGV current position information stored in a storage unit of an automatic guided vehicle AGV of the present invention; FIG. 4 is an explanatory diagram of one embodiment of AGV point group information stored in a storage unit of an automatic guided vehicle AGV of the present invention; FIG. 4 is an explanatory diagram of one embodiment of obstacle information stored in a storage unit of the automatic guided vehicle AGV of the present invention; FIG. 5 is an explanatory diagram of another embodiment of AGV point cloud information stored in the storage unit of the automatic guided vehicle AGV of the present invention; FIG. 4 is an explanatory diagram of an example of map coordinates obtained by superimposing MV position information and AGV point group information; FIG. 10 is an explanatory diagram of another embodiment of MV position selection information stored in the storage unit of the automatic guided vehicle AGV of the present invention; FIG. 10 is an explanatory diagram of an embodiment of map coordinates obtained by superimposing MV point group information and MV position selection information; FIG. 4 is an explanatory diagram of one embodiment of MV point group correction information stored in the storage unit of the automatic guided vehicle AGV of the present invention; FIG. 4 is an explanatory diagram of one embodiment of obstacle information obtained by synthesizing MV point group correction information and AGV point group information stored in a storage unit of an automatic guided vehicle AGV according to the present invention; FIG. 10 is an explanatory diagram of an example of MV correction position information generated using MV correction position information and point cloud deviation amount; FIG. 2 is an explanatory diagram of an embodiment when a manned guided vehicle MV and an unmanned guided vehicle AGV with LiDARs of this invention having different heights are viewed from the side. FIG. 2 is an explanatory diagram of an embodiment when a manned guided vehicle MV equipped with LiDAR and an unmanned guided vehicle AGV equipped with a laser light receiving section of the present invention are viewed from the side;

In an embodiment of the present invention, in particular, a vehicle travel management system includes an obstacle detection sensor that measures the distance to an obstacle present in the traveling direction of the manned vehicle to detect the position of the obstacle, and a manned travel control system. The unmanned vehicle is detected from an encoder that measures the number of rotations of the wheels of the vehicle and the rotation angle of the steering wheel, the movement of the vehicle body of the manned vehicle calculated from the encoder, and the obstacle information detected by the obstacle detection sensor. Using the map information of the spatial area used for self-position estimation, information on the current position and traveling direction of the self on the map of the spatial area is obtained by calculations equivalent to those performed by the unmanned vehicle. and a self-position estimating unit for estimating.

Further, the manned vehicle further includes a self-position information transmitting unit that transmits current position information regarding the current position and traveling direction of the self on the map of the spatial region estimated by the self-position estimating unit, The information is transmitted to the unmanned vehicle by wireless communication, or the current position information is transmitted to the unmanned vehicle traveling in the same spatial area by wireless communication by broadcasting.

In addition, the unmanned vehicle has a vehicle approach determination unit that calculates the distance to another vehicle and determines whether another vehicle is approaching the own vehicle, and a travel stop unit that stops the self travel. and, when the vehicle approach determination unit determines that the manned vehicle has approached within a predetermined distance, the travel stop unit stops its own travel.

Further, the unmanned vehicle determines the manned vehicle from current position information of the manned vehicle acquired by the position information acquisition unit and shape information representing the external shape of the manned vehicle by point cloud information. From the manned vehicle point cloud information generation unit that generates the first point cloud information indicating the current attitude of the manned vehicle, the distance measurement information of the own unmanned vehicle, and the information on the current position and traveling direction of the own unmanned vehicle a self-point-group information generating unit for generating second point-group information indicating the position of an object detected as an obstacle; synthesizing the first point-group information and the second point-group information; It is characterized by further comprising a point group synthesizing unit that generates obstacle information including the current position of the manned vehicle.

Embodiments of the present invention will be described below with reference to the drawings. It should be noted that the present invention is not limited by the description of the following examples.
The vehicle running management system of the present invention is a system for managing the running of manned and unmanned vehicles so that they do not collide in a predetermined area. It consists of a manned vehicle, an unmanned vehicle, and a running management device, and the manned vehicle and the unmanned vehicle are vehicles that run inside buildings such as factories and warehouses, or within predetermined premises. .

In the following embodiments, a vehicle travel management system including manned guided vehicles and unmanned guided vehicles that travel in a warehouse or the like having a large number of product shelves to transport and store products will be described.
A manned guided vehicle corresponds to a manned traveling vehicle, and an unmanned guided vehicle corresponds to an unmanned traveling vehicle.

<Configuration of vehicle travel management system>
FIG. 1 shows a schematic block diagram of the vehicle running management system of the present invention.
In FIG. 1, the vehicle running management system comprises a running management device 1, one or more manned guided vehicles 2, and one or more unmanned guided vehicles 3. As shown in FIG.
A manned guided vehicle 2 (MV) is a vehicle that travels under human driving operation, an unmanned guided vehicle 3 (AGV) is a vehicle that can autonomously travel, and a travel management device 1 (SV) operates in the same spatial area. It is a device that manages the travel of manned and unmanned guided vehicles that travel.
Each manned guided vehicle 2, each unmanned guided vehicle 3, and the travel management device 1 are connected via a network 4 and can communicate with each other.
The network 4 can use any existing network such as a WAN such as the Internet or a LAN.

The travel management device 1 has a wired communication function or a wireless communication function, and is connected to the network 4 by either wired communication or wireless communication.
The manned guided vehicle 2 and the unmanned guided vehicle 3 shall have a wireless communication function and be connected to the network 4 by wireless communication so that they can move freely.

The travel management device 1 (SV) is an information processing device having a travel control function of an unmanned guided vehicle, a function of acquiring the current positions of manned and unmanned guided vehicles, a collision avoidance function of each vehicle, and the like.
The manned guided vehicle 2 (MV) is a vehicle on which a person rides and which is driven by a person, such as a forklift, a four-wheeled vehicle, and a luggage carrier.
The automated guided vehicle 3 (AGV) is a vehicle capable of autonomous travel, and travels along a predetermined travel route based on a travel instruction signal from the travel management device 1 .

In the vehicle travel management system of the present invention, travel control of the manned guided vehicle and the unmanned guided vehicle is mainly performed by the following processing.
The distance and the initial position that the manned guided vehicle moved from the initial position when it was started, which is calculated using the map information of the space area in which it travels, which is stored in advance, and the measured number of rotations of the wheels and the rotation angle of the steering wheel. on the map of the space area from the first cumulative movement amount consisting of the angle change amount from the initial bearing in Estimates information about its current position and heading.

The distance traveled by the automated guided vehicle from the initial position and the angle from the initial azimuth at the initial position calculated using map information of the spatial region in which the vehicle travels and the measured number of rotations of the wheels. current position and progress on the map of the space area based on the second cumulative movement amount consisting of the amount of change, distance measurement information to obstacles existing in the direction of travel, and information on the position of the detected obstacles. Estimate information about orientation.

The travel management device acquires AGV position information indicating the current position and traveling direction of the unmanned guided vehicle and MV position information indicating the current position and traveling direction of the manned guided vehicle, and uses the AGV position information and the MV position information. Then, it is determined whether or not the automatic guided vehicle and the manned guided vehicle are approaching each other, and the operation of the automatic guided vehicle is controlled based on the determination result of the approach.

FIG. 5 shows an explanatory diagram of an embodiment of a region where manned vehicles and unmanned vehicles travel.
The travel area in FIG. 5 shows a schematic map of a warehouse in which a large number of product shelves 5 are arranged. It shows how the robot travels up, down, left, and right between product shelves 5 .
As will be described later, manned and unmanned guided vehicles calculate their current self-position and traveling direction on a map in the space area of the warehouse, and the calculated current self-position (current position) and traveling direction information is It is transmitted to the running management device 1 periodically.
The travel management device 1 uses the received information such as the current position of each manned vehicle and each automatic guided vehicle to control the travel of each unmanned guided vehicle so that the vehicles do not collide.

For example, the travel management device 1 transmits a stop instruction signal requesting the automatic guided vehicles (AGV1, AGV2, AGV3) existing in the traveling direction of the manned guided vehicle MV1 in FIG. 5 to stop, or A collision is avoided by transmitting a retraction instruction signal for retracting to a position that does not interfere with the traveling of the manned guided vehicle MV1.
On the other hand, the travel management device 1 indicates that an unmanned guided vehicle AGV exists within a predetermined distance in the traveling direction of the manned guided vehicle MV1, so it should travel with caution, and an unmanned guided vehicle that exists within a predetermined distance. Sends warning information indicating the location of the guided vehicle (AGV1, AGV2, AGV3) on the map.

(Schematic configuration of manned guided vehicle)
6 and 7 show schematic perspective views of an embodiment of the manned guided vehicle of the present invention.
Here, a schematic perspective view of a forklift that is the manned transport vehicle 2 is shown.
In FIG. 6, the forklift 2 includes a headlamp F1, a flasher lamp F2, a mast F3, a backrest F4, a fork F5, and road wheels F6.
7, the forklift 2 includes a head guard F7, a handle F8, an inspection cover F9, a battery F10, a brake pedal F11, wheels F12, and caster wheels F13.
A driver on the forklift 2 operates the handle F8 to drive the wheels F12 to move forward, backward, and turn.

8 and 9 show schematic configuration layout diagrams of an embodiment viewed from the top of a manned transport vehicle (forklift).
Arrows in FIGS. 8 and 9 indicate the forward direction of the forklift.
FIG. 8 shows the arrangement of the vehicle speed encoder 43, the rotation angle encoder 45, and the obstacle detector (LiDAR) 48 in addition to the road wheel F6, steering wheel F8, and wheel F12 described above.

The vehicle speed encoder 43 is attached to the wheel F12, which is a driving wheel, and measures the number of rotations, the direction of rotation, the speed of rotation, and the like of the wheel.
The rotation speed measured by the vehicle speed encoder 43 is called wheel rotation speed.
A rotation angle encoder 45 is attached to the handle F8 and measures the rotation angle of the handle.
The rotation angle of the steering wheel measured by the rotation angle encoder 45 is called the steering wheel rotation angle.
By using the wheel rotation speed and the steering wheel rotation angle, the cumulative displacement from a predetermined initial position is measured.
Furthermore, the self-position of the forklift on the map is estimated using the map information, the cumulative amount of movement, and distance measurement information obtained from LiDAR, which will be described later.

The obstacle detection unit 48 is a device that detects obstacles existing in the traveling direction of the forklift, and in the present invention, LiDAR is used.
The LiDAR48 is a device that measures the distance from the current position of the forklift to an object or road surface that exists within a predetermined space in the direction in which the forklift is traveling, and is placed near the center of the front portion of the vehicle body housing.
The LiDAR 48 has a light emitting part that emits laser light in a predetermined area in the direction of travel, a light receiving part that receives laser light reflected by an object, and a scanning device that changes the direction of laser light emission two-dimensionally or three-dimensionally. It consists of a control unit.

After a laser beam is emitted from the light-emitting part into a two-dimensional space or a three-dimensional space within a predetermined obstacle detection area, the reflected light reflected by the object is detected by the light-receiving part. , the light-receiving distance traveled by the laser beam is calculated. The distance (distance measurement information) to the object (obstacle) is measured from the calculated light receiving distance.
In addition, the LiDAR 48 acquires information (point group information) regarding distances at a plurality of measurement points within the obstacle detection area by changing the emission direction of the laser light using the scanning control unit. The shape and existing position of the obstacle are detected from the point group information.

FIG. 8 shows a configuration layout diagram in which one LiDAR is arranged as the obstacle detection unit 48. In FIG. 9, LiDAR 48 1 shows a configuration layout diagram in which the .
For example, a LiDAR placed on the left face detects obstacles to the left, and a LiDAR placed on the right face detects obstacles to the right.
By detecting obstacles in three directions in this manner, blind spots can be reduced, and collisions can be avoided more reliably.
In addition, as will be described later, the information obtained from the LiDAR is used to estimate the current position of the forklift itself. By using the information obtained from the three LiDARs, the accuracy of self-position estimation is improved. can be made

(Schematic configuration of automatic guided vehicle)
FIG. 10 shows a schematic configuration layout diagram of an embodiment of an automatic guided vehicle (AGV) of the present invention viewed from above.
FIG. 11 shows a schematic configuration layout diagram of an embodiment viewed from the side of an automatic guided vehicle (AGV) of the present invention.
Arrows in FIGS. 10 and 11 indicate the forward direction of the automatic guided vehicle AGV.

10 and 11 show the arrangement of left wheel A1, right wheel A2, caster A3, and motor A4, which are main components of the automatic guided vehicle.
Also shown are the encoders 73 that measure the rotation speeds of the left wheel A1 and the right wheel A2, respectively, and the LiDAR 75 that corresponds to the obstacle detector 75 .
A left wheel A1 and a right wheel A2 are drive wheels driven by a motor A4, and a caster A3 is a driven wheel.
The LiDAR 75 measures the distance to obstacles in the forward direction of the unmanned guided vehicle AGV, and detects the shape and position of the obstacles.

<Configuration of functions of travel management device>
FIG. 2 shows an explanatory diagram of the functional configuration of one embodiment of the running management system 1 of the present invention.
2, the driving management device 1 (SV) mainly includes a control unit 11, an operation unit 12, a display unit 13, a communication unit 14, an AGV position information acquisition unit 21, an MV position information acquisition unit 22, and a vehicle approach determination unit 23. , an AGV operation control unit 24 , a warning notification unit 25 , and a storage unit 30 .

The control unit 11 is a portion that controls the operation of each component such as the operation unit and the display unit, and is mainly implemented by a microcomputer including a CPU, ROM, RAM, I/O controller, timer, and the like.
The CPU organically operates various hardware based on a control program pre-stored in the ROM or the like, and executes the communication function of the travel management device 1, the travel management function of the vehicle, and the like.

The operation unit 12 is a part where a user of the travel management device 1 inputs information, and is an input device for performing a predetermined input operation for controlling the operation of the automatic guided vehicle AGV. For example, it is a part for inputting information such as characters and for selecting and inputting functions, and a keyboard, mouse, touch panel, etc. are used.
Keys operated by the user include an operation start key, a function selection key, a setting key, and the like.

The display unit 13 is a part that displays information, and displays information necessary for executing each function, the result of executing the function, and the like in order to inform the user. For example, when an LCD, an organic EL display, or the like is used, and a touch panel is used as the operation unit 12, the display unit 13 and the touch panel are arranged so as to overlap each other.
The display unit 13 displays, for example, the contents of setting items used for travel control of the automatic guided vehicle AGV, information necessary for executing the travel control function, an operation screen for the selected function, settings for travel items, and so on. Operation screens and the like are displayed using characters, symbols, graphics, images, icons, animations, moving images, and the like.

The communication unit 14 is a part that communicates information via the network 4, and performs data communication with the manned guided vehicle MV and the unmanned guided vehicle AGV.
For example, it receives information about the current position transferred from a manned guided vehicle MV or an unmanned guided vehicle AGV.
In addition, it transmits a stop request signal and a travel instruction signal to the automatic guided vehicle AGV, and transmits warning information to the manned guided vehicle MV.

The AGV position information acquisition unit 21 acquires information (AGV current position information) indicating the current position and traveling direction of the automatic guided vehicle transmitted from the automatic guided vehicle AGV, and stores it in the storage unit 30 as AGV position information 32. part.
Since the AGV current position information is transmitted from each automatic guided vehicle AGV at regular time intervals, the stored AGV position information 32 is also updated each time.
Alternatively, the AGV position information 32 may be stored as a history together with the reception time of the AGV current position information.
The AGV position information 32 includes the position coordinates on the map, which is the current position of the automatic guided vehicle, and the azimuth indicating the traveling direction.

The MV position information acquisition unit 22 acquires information (current position information) indicating the current position and traveling direction of the manned guided vehicle MV transmitted from the manned guided vehicle MV, and stores the information in the storage unit 30 as MV position information 33. is.
Since current position information is transmitted from each manned guided vehicle MV at regular time intervals, the stored MV position information 33 is also updated each time.
Alternatively, the MV position information 33 may be stored as a history along with the reception time of the current position information.
The MV position information 33 includes the position coordinates on the map, which is the current position of the manned guided vehicle MV, and the azimuth indicating the traveling direction.

It is preferable to determine the transmission period of the current position information in consideration of the running speed of the vehicle. Since high-speed manned guided vehicles MV travel long distances in a short period of time, position information is transmitted in as short a cycle as possible. not. By setting the transmission cycle according to the running speed in this way, it is possible to effectively use the network communication band.

The vehicle approach determination unit 23 corresponds to the first vehicle approach determination unit described above, and uses the AGV position information 32 of the automatic guided vehicle AGV and the MV position information 33 of the manned guided vehicle MV to determine the automatic guided vehicle AGV and This is the part that determines whether or not the manned guided vehicle MV is approaching.
In response to the approach determination result, it controls the operation of the automatic guided vehicle AGV and notifies warning information to the manned guided vehicle MV.

For example, it is determined whether or not the distance between two vehicles traveling in the area shown in FIG. 5 is shorter than a predetermined set distance. On the other hand, if the distance is longer than the predetermined set distance, it is determined that the two vehicles are not approaching each other.
In addition, it is determined whether the current inter-vehicle distance between the two vehicles is shorter than the inter-vehicle distance used in the previous determination, and the current inter-vehicle distance is the inter-vehicle distance used in the previous determination. If it is shorter than the distance, it is determined that both vehicles are approaching, and if it is longer, it is determined that both vehicles are moving away.
An embodiment of vehicle approach determination and travel control processing in this travel management device will be described later.

The AGV operation control unit 24 is a part that controls the operation of the automatic guided vehicle AGV. Control.

In addition, the vehicle approach determination unit 23 of the travel management device uses information about the current position and traveling direction of the unmanned guided vehicle estimated on the map of the same spatial area and information about the current position and traveling direction of the manned guided vehicle. Then, when it is determined that the automatic guided vehicle and the manned guided vehicle are approaching within a predetermined distance, the AGV operation control unit 24 adjusts the automatic guided vehicle so that the automatic guided vehicle and the manned guided vehicle do not collide. to control.
For example, when it is determined that a manned guided vehicle MV and an unmanned guided vehicle AGV are approaching, an instruction to stop the approaching unmanned guided vehicle AGV is sent, or an instruction to run to a predetermined evacuation location. to send.

More specifically, as will be described later, when the vehicle approach determination unit 23 determines that the inter-vehicle distance between the unmanned guided vehicle and the manned guided vehicle is shorter than the unconditional stopping distance L0, the unmanned guided vehicle is stopped. good too.
Further, when the vehicle-to-vehicle distance between the unmanned guided vehicle and the manned guided vehicle is equal to or greater than the unconditional stopping distance L0 and shorter than the conditional stopping distance L1, the vehicle approach determination unit 23 determines that the unmanned guided vehicle and the manned guided vehicle When it is determined that the automatic guided vehicle is in an approaching state in which it is traveling in a direction in which the automatic guided vehicle is approaching, the automatic guided vehicle may be stopped.
Alternatively, when the vehicle-to-vehicle distance between the unmanned guided vehicle and the manned guided vehicle is equal to or greater than the unconditional stopping distance L0 and shorter than the conditional stopping distance L1, the vehicle approach determination unit 23 determines that the unmanned guided vehicle and the manned guided vehicle When it is determined that the automatic guided vehicle is in a separated state in which the vehicle is moving away from the vehicle, the automatic guided vehicle may be decelerated.

By controlling the operation of the automatic guided vehicle AGV, collision between the automatic guided vehicle AGV and the manned guided vehicle MV can be prevented, and safe operation of the entire vehicle travel management system can be achieved.

The warning notification unit 25 is a part that notifies the manned guided vehicle MV of warning information in accordance with the result of the approach determination.
For example, when the vehicle approach determination unit 23 determines that the unmanned guided vehicle AGV and the manned guided vehicle MV are approaching within a predetermined distance, the manned guided vehicle MV is approaching the unmanned guided vehicle AGV. and alert information indicating the presence of an unmanned guided vehicle (AGV) nearby.
Alternatively, warning information indicating the risk of collision with the automatic guided vehicle AGV, the distance to the automatic guided vehicle AGV, the direction, etc. may be sent to the manned guided vehicle MV.
By issuing such a warning notification to the manned guided vehicle MV, it is possible to alert the driver of the manned guided vehicle MV and drive safely so that the vehicle does not collide.

The storage unit 30 is a part that stores information and programs necessary for executing each function of the travel management device 1, and includes semiconductor storage elements such as ROM, RAM, and flash memory, storage devices such as HDD and SSD, and other storage devices. of storage media are used.
The storage unit 30 stores, for example, map information 31, AGV position information 32, MV position information 33, approaching vehicle information 34, vehicle current position information 35, and the like.
In addition, the unconditional stopping distance L0 and the conditional stopping distance L1 are preset and stored in the storage unit 30 as criteria for determining whether or not the vehicle is approaching.

The map information 31 is a map of an area managed by the travel management device 1, and is information of a spatial area in which the automatic guided vehicle AGV and the manned guided vehicle MV travel.
The map information 31 includes, for example, information about the routes traveled by the automated guided vehicle AGV and the manned guided vehicle MV and the positions of product shelves and the like.
A position on the map is specified by position coordinates (X coordinate, Y coordinate) from an initial point that serves as a predetermined reference.
The travel management device 1 controls travel of the automatic guided vehicle AGV based on the map information 31 and identifies the current positions of the automatic guided vehicle AGV and the manned guided vehicle MV.
Automated guided vehicles AGV and manned guided vehicles MV also store the same map information, and use this map information to estimate their own current positions.

As described above, the AGV position information 32 is information obtained by the AGV position information obtaining unit 21 at regular intervals, and includes the position coordinates on the map, which is the current position of the automatic guided vehicle AGV, and the azimuth indicating the traveling direction. and are included.
The positional coordinates on the map are the positional coordinates (X coordinate, Y coordinate) in the map information 31 .
The azimuth indicating the direction of travel is information indicating the orientation of the vehicle on the map, and is, for example, the angle between the vehicle and the X coordinate.
From the AGV position information 32, the current position where the automatic guided vehicle AGV exists and the direction in which it is traveling can be known.

As described above, the MV position information 33 is information obtained by the MV position information obtaining unit 22 at regular intervals. and are included.
As with the AGV position information 32, the position coordinates on the map are the position coordinates (X coordinates, Y coordinates) in the map information 31, and the orientation indicating the direction of travel is information indicating the orientation of the vehicle on the map. , is the angle between the body and the X coordinate.
From the MV position information 33, the current position where the manned guided vehicle MV exists and the direction in which it is traveling can be known.

The approaching vehicle information 34 is information about vehicles in a predetermined approaching state, and information (vehicle name, current position, orientation, etc.) of two or more vehicles determined to be in an approaching state by the vehicle approach determination unit 23 . and the distance between those vehicles.
When the automatic guided vehicle AGV is stopped, information indicating that the automatic guided vehicle AGV has been stopped may also be included.

The vehicle current position information 35 is position coordinates indicating the current positions of all automatic guided vehicles AGVs and manned guided vehicles MVs managed by the running management device 1, and is information obtained from the AGV position information 32 and the MV position information 33. .
The position coordinates are used to calculate the distance between the vehicles, and to display the current position of each vehicle on the map screen displayed on the display unit 13 .

<Configuration of manned guided vehicle functions>
FIG. 3 shows a functional configuration explanatory diagram of an embodiment of the manned guided vehicle 2 of the present invention.
3, the manned guided vehicle 2 (MV) mainly includes a control unit 41, a vehicle speed measurement unit 42, a vehicle speed encoder 43, a traveling direction measurement unit 44, a rotation angle encoder 45, a wireless communication unit 46, a movement amount calculation unit 47, An obstacle detection unit 48 , a self-position estimation unit 49 , a self-position information transmission unit 50 , a warning acquisition unit 51 and a storage unit 60 are provided.

The control unit 41 is a part that controls the operation of each component such as the obstacle detection unit 48 and the self-position estimation unit 49. Mainly, a microcomputer consisting of a CPU, ROM, RAM, I/O controller, timer, etc. Realized.
The CPU organically operates various hardware based on a control program pre-stored in the ROM or the like, and executes the communication function and the self-position estimation function of the manned guided vehicle MV.
Also, like the forklift described above, in principle, a driver rides on a manned guided vehicle MV, and the control unit 41 controls the rotation speed and traveling direction of the wheels based on the driver's steering wheel operation, accelerator and brake operation. Control.

As described above, the vehicle speed encoder 43 is attached to the wheel F12, which is the drive wheel, and measures the rotation speed of the wheel F12 (wheel rotation speed).
The measured wheel rotation speed is provided to the vehicle speed measurement unit 42 .

The vehicle speed measurement unit 42 is a part that calculates the travel speed of the manned guided vehicle MV from the wheel rotation speed measured by the vehicle speed encoder 43 .
Also, the travel distance may be calculated from the travel speed and the travel time.
The travel speed or travel distance is given to the movement amount calculation unit 47 at regular time intervals.

As described above, the rotation angle encoder 45 is attached to the handle F8 and measures the rotation angle of the handle F8 (handle rotation angle).
The measured steering wheel rotation angle is given to the traveling direction measuring section 44 .

The traveling direction measuring unit 44 is a part that calculates the traveling direction (body direction) of the manned guided vehicle MV from the steering wheel rotation angle measured by the rotation angle encoder 45 .
The steering wheel rotation angle is the angle at which the driver turns the steering wheel, and the current running direction (body direction) is calculated from the turning angle from the reference direction.
The traveling direction (body direction) is given to the movement amount calculation unit 47 at regular time intervals.

The wireless communication unit 46 is a part that communicates information via the network 4, and performs data communication with the travel management device SV and the automatic guided vehicle AGV.
Since the manned guided vehicle MV is a vehicle that moves in a predetermined area, it communicates data wirelessly.
For example, it receives current position information transferred from the automatic guided vehicle AGV, and receives warning information sent from the travel management device SV. Also, the current position information of the manned guided vehicle MV is transmitted to the travel management device SV.

As a form of wireless communication of the manned guided vehicle MV, it is preferable to be able to perform wireless communication between devices at relatively long distances, such as wireless communication of a mobile phone or the like.
However, for the communication between the manned guided vehicle MV and the unmanned guided vehicle AGV, proximity wireless communication such as Bluetooth or infrared communication may be used.
When sending the location information of the manned guided vehicle MV using Bluetooth or infrared communication, the location information of the manned guided vehicle MV is sent only to AGVs that exist near the manned guided vehicle MV. is transmitted more frequently without affecting the overall radio bandwidth of the system. Therefore, even when the connection state of wireless communication is not good, it is possible to reliably transmit data such as position information between the manned guided vehicle MV and the unmanned guided vehicle AGV.

Further, as the radio communication function of the manned guided vehicle MV, both a long-distance radio communication function and a short-distance radio communication function such as close proximity radio communication may be provided.
For example, information can be transmitted infrequently to a driving management device SV or a distant AGV using a long-distance wireless communication function, and information can be sent to a nearby automatic guided vehicle AGV. The information may be transmitted at high frequency using the wireless communication function of the distance.
In this way, by sending the rough travel position of the manned guided vehicle MV to the travel management device SV and sending the detailed travel position of the manned guided vehicle MV to the nearby unmanned guided vehicle AGV, More efficient information transmission becomes possible.

The movement amount calculation unit 47 is a part that calculates the cumulative amount of movement from the initial position at which the manned guided vehicle MV is started.
Using the traveling speed or traveling distance given by the vehicle speed measuring section 42 and the traveling direction (vehicle bearing) given by the traveling direction measuring section 44, the cumulative amount of movement from the initial position is calculated.
The initial position when the manned guided vehicle MV is activated corresponds to the stationary position before activation, and is represented by the position coordinates (X coordinate, Y coordinate) with the reference point of the map showing the travel area as the origin. , The position coordinates of this initial position on the map are stored in advance, or are set by the MV operator or the SV operator after activation.

The cumulative movement amount corresponds to the first cumulative movement amount described above, and is information calculated using the measured number of rotations of the wheels and the rotation angle of the steering wheel. It consists of the distance moved from the position coordinates (movement distance) and the amount of angular change from the initial orientation at the initial position, and stores, for example, the running speed and orientation measured at regular intervals as a history.
The route from the initial position to the current position can be specified from the history of the traveling speed and direction, and the position coordinates and traveling direction (vehicle direction) of the current position of the manned guided vehicle MV can be determined from the position coordinates of the initial position and the cumulative amount of movement. is required.
The position coordinates (X coordinate, Y coordinate) of the current position of the manned vehicle MV are information indicating the position of the center of gravity of the manned vehicle MV.
Also, the calculated cumulative movement amount is given to the self-position estimation unit 49 as the cumulative movement amount information 64 .

As already explained, the obstacle detection unit 48 measures the distance measurement information (corresponding to the first distance measurement information described above) to an obstacle existing in the traveling direction of the manned guided vehicle MV, and determines the position of the obstacle. and uses a LiDAR that emits laser light.
Distance information to obstacles is measured by LiDAR, and obstacles are detected from the distance information. The distance measurement information and information on the detected obstacles are provided to the self-position estimating section 49 .
The obstacle detection section 48 corresponds to the first obstacle detection section described above.

The distance to the obstacle and the shape of the obstacle can be obtained from the ranging information from the LiDAR.
Generally, when traveling in a warehouse, obstacles such as walls and product shelves on the travel route are detected, and other manned guided vehicles MV and unmanned guided vehicles AGV are also detected as obstacles.
Assuming that the position coordinates and shapes of obstacles such as walls and product shelves on the travel route on the map are stored in advance, the obtained shape of the obstacle is compared with the shape of the obstacle on the map. By doing so, the detected obstacle is recognized, and from the obtained distance to the obstacle and the position coordinates of the recognized obstacle on the map, the approximate current position of the manned guided vehicle MV on the map Position coordinates can be obtained.

The self-position estimation unit 49 is a part that estimates the current position on the map where the manned guided vehicle MV exists.
The map information stored in the storage unit 60, the cumulative movement amount calculated by the movement amount calculation unit 47, the distance measurement information measured by the obstacle detection unit (LiDAR) 48, and the detected obstacle (For example, position coordinates of obstacles on the map), the current position of the space area in which the manned guided vehicle MV travels is estimated, and information about its own current position and traveling direction on the map of the space area to get
The self-position estimation unit 49 corresponds to the first self-position estimation unit described above.

The acquired information about the current position of the manned vehicle MV on the map includes the position coordinates (X coordinates, Y coordinates) of the current position of the manned vehicle MV and the traveling direction (body direction).
Information consisting of the position coordinates (X coordinates, Y coordinates) of the current position and the traveling direction (body direction) is called current position information or posture information.
The acquired current position information of the manned guided vehicle MV is given to the self-position information transmitting unit 50 .

As described above, the position coordinates of the current position of the manned guided vehicle MV on the map and the traveling direction (body direction) can be obtained from the position coordinates of the initial position and the accumulated movement amount.
However, there may be an error between the calculated accumulated travel distance and direction and the actual travel distance and direction due to slippage of the wheels of the manned guided vehicle MV, error in wheel rotation speed, road surface conditions, etc. may accumulate.

Therefore, using the information from the obstacle detection unit 48, the position coordinates and traveling direction of the current position of the manned guided vehicle MV on the map obtained from the accumulated movement amount etc. are corrected, and the current position of the manned guided vehicle MV is corrected. to estimate
That is, from the distance measurement information measured by the obstacle detection unit 48 and the position coordinates of the detected obstacles on the map, the position coordinates on the map of the current position of the manned guided vehicle MV are acquired, and the accumulated movement is calculated. Correct the position coordinates and traveling direction of the current position on the map of the manned guided vehicle MV acquired from the amount.

For example, the position coordinates of the current position of the manned guided vehicle MV on the map obtained from the accumulated movement amount or the like may be converted into the position coordinates of the current position on the map obtained by the obstacle detection unit 48 .
Alternatively, the position coordinates of the current position on the map of the manned guided vehicle MV obtained from the accumulated movement amount or the like may be corrected using the position coordinates of the current position on the map obtained by the obstacle detection unit 48. good.

In this way, the position coordinates of the current position of the manned guided vehicle MV on the map obtained from the accumulated amount of movement calculated from the wheel rotation speed and the steering wheel rotation angle, and the current position on the map obtained by the obstacle detection unit 48 By estimating the current position of the manned guided vehicle MV using the positional coordinates, it is possible to reduce the error between the calculated cumulative movement distance and direction and the actual movement distance and direction. can.

The self-position information transmission unit 50 is a part that transmits current position information regarding the self's current position and traveling direction on the map of the spatial area estimated by the self-position estimation unit 49 of the manned guided vehicle MV. The current position information is sent to, for example, the travel management device SV.
The current position information of the manned guided vehicle MV consists of the position coordinates (X coordinate, Y coordinate) of the current position of the manned guided vehicle MV and the traveling direction (vehicle direction). From the information, it is possible to know the position of the manned guided vehicle MV on the map of the travel area and the direction in which it is traveling.
This current position information may be transmitted to the running management device SV by wireless communication, or may be transmitted to the running management device SV and the automatic guided vehicle AGV traveling in the same spatial area by wireless communication by broadcasting.

The current position information of the manned guided vehicle MV is preferably transmitted by designating the travel management device SV as the destination so that the travel management device SV can manage the current position of the manned guided vehicle MV.
The travel management device SV that has received the current position information of the manned guided vehicle MV, for example, uses the received current position information to control the travel of the unmanned guided vehicle AGV so that the vehicles do not collide with each other.

Also, the current position information of the manned guided vehicle MV may be transmitted to the network 4 by so-called broadcasting without specifying the destination.
When the current location information is transmitted by broadcasting, all devices connected to the network 4 can receive the broadcasted current location information.
For example, in addition to the travel management device SV, other manned guided vehicles MV and unmanned guided vehicles AGV connected to the network 4 can also receive the current position information.

When the automatic guided vehicle AGV receives the current position information of the manned guided vehicle MV, for example, the current position of the automatic guided vehicle AGV itself and the current position of the manned guided vehicle MV obtained from the current position information By comparison, if the two vehicles are close to each other, the automatic guided vehicle AGV stops its own traveling or retreats to a position that does not interfere with the traveling of the manned guided vehicle MV.
In this way, when the current position information of the manned guided vehicle MV is broadcast, the automatic guided vehicle AGV that receives the current position information controls its own running, thereby ensuring the safety of the manned guided vehicle MV and the unmanned guided vehicle AGV. It is possible to ensure a smooth running.

The warning acquisition unit 51 is a part that acquires warning information transmitted from the travel management device SV and notifies the driver of the manned guided vehicle MV.
When the travel management device SV determines that a vehicle is approaching, predetermined warning information is transmitted to the manned guided vehicle MV approaching another vehicle.
When the manned guided vehicle MV acquires warning information, if the manned guided vehicle is equipped with a display device, the warning information is displayed on the display screen to notify the driver of the manned guided vehicle MV of the risk of collision. The system notifies the driver with character information that the driver should slow down and drive safely.
Alternatively, if the manned guided vehicle MV is equipped with a speaker, the acquired warning information is converted into audio data to inform the driver of the manned guided vehicle MV that there is a risk of collision and that the driver should slow down. It notifies you by voice that you should drive safely.

The storage unit 60 is a part that stores information and programs necessary for executing each function of the manned guided vehicle MV. of storage media are used.
The storage unit 60 corresponds to the above-described first storage unit.
The storage unit 60 stores, for example, map information 61, wheel rotation speed 62, steering wheel rotation angle 63, accumulated movement amount information 64, distance measurement information 65, current position information 66, and the like.

The map information 61 is information of the spatial area in which the manned guided vehicle MV travels, and as described above, is the same information as the map information stored in the travel management device SV. 61 to estimate its own current position.

The wheel rotation speed 62 (FD1) is the rotation speed of the wheel F12 measured by the vehicle speed encoder 43, as described above, and is always measured.

The steering wheel rotation angle 63 (FD2) is the rotation angle of the steering wheel F8 measured by the rotation angle encoder 45, as described above, and is always measured.

The cumulative movement amount information 64 (FD3) is information calculated by the movement amount calculation unit 47 as described above, and is the distance (movement distance) moved from the position coordinates of the initial position of the manned guided vehicle MV and the initial position and the amount of angular change from the initial orientation in .

The ranging information 65 (FD4) is information acquired from LiDAR and is information indicating the distance to an obstacle.
LiDAR can acquire a plurality of ranging information by scanning laser light horizontally and vertically, and the acquired plurality of ranging information is also called point cloud information.
From this point group information, the distance to obstacles in the running direction and the shape of the obstacles can be obtained.

The current position information 66 (FD5) is information output from the self-position estimation unit 49, as described above, and includes the position coordinates (X coordinates, Y coordinates) of the current position of the manned guided vehicle MV and the traveling direction (vehicle body direction).

<Explanation of self-position estimation processing of manned guided vehicle>
FIG. 14 shows a configuration block diagram of an embodiment related to self-position estimation processing of a manned guided vehicle (forklift).
A forklift, which is a manned vehicle MV, has a vehicle speed encoder 43 and a rotation angle encoder 45, as already described with reference to FIG.
A wheel rotation speed 62 is output to the movement amount calculation unit 47 from the vehicle speed encoder 43 attached to the wheel F12.
A handle rotation angle 63 is output to the movement amount calculator 47 from the rotation angle encoder 45 attached to the handle F8.

The movement amount calculation unit 47 uses the input wheel rotation speed 62 and the steering wheel rotation angle 63 to calculate accumulated movement amount information 64 and provides it to the self-position estimation unit 49 .
The cumulative movement amount information 64 consists of the distance (movement distance) moved from the position coordinates of the initial position of the manned guided vehicle MV and the amount of angular change from the initial orientation at the initial position, and is obtained from the rotation of the wheels and the operation of the steering wheel. It is the information

On the other hand, when the LiDAR corresponding to the obstacle detection unit 48 detects an obstacle, the LiDAR provides the distance measurement information 65 to the self-position estimation unit 49 .

The self-position estimation unit 49 refers to the map information 61 stored in the storage unit 60, corrects the accumulated movement amount information 64 using the accumulated movement amount information 64 and the distance measurement information 65, and corrects the accumulated movement amount information 64. MV current location information 66 is generated.

The current position information 66 of the manned guided vehicle MV is transmitted to the network 4 by the self-position information transmission unit 50 .
When the destination is set to the travel management device SV, the current position information 66 is sent only to the travel management device SV.
On the other hand, if the current position information 66 is broadcast without setting the destination, the current position information 66 is sent.

As described above, the current position of the manned guided vehicle MV is calculated using not only the distance measurement information 65 output from the LiDAR, but also the cumulative movement amount information 64 calculated using the number of rotations of the wheels and the rotation angle of the steering wheel. Therefore, information on the current position of the manned guided vehicle MV can be obtained with higher accuracy. It is possible to reduce the possibility of collision between the traveling automatic guided vehicle AGV and the manned guided vehicle MV.

<Functional Configuration of Automatic Guided Vehicles>
FIG. 4 shows a functional configuration explanatory diagram of an embodiment of the automatic guided vehicle 3 of the present invention.
4, the automatic guided vehicle 3 (AGV) of the present invention mainly includes a control section 71, an AGV movement amount calculation section 72, an encoder 73, a laser light receiving section 74, an obstacle detection section 75, a wireless communication section 76, a self position Estimation unit 77 , self-location information transmission unit 78 , MV location information acquisition unit 79 , point cloud information generation unit 80 , point cloud information selection unit 81 , point cloud synthesis unit 82 , point cloud information comparison unit 83 , MV location correction unit 84 , a vehicle approach determination unit 85 , an attribute information addition unit 86 , a request information acquisition unit 87 , a travel stop unit 88 , and a storage unit 100 .

The control unit 71 is a part that controls the operation of each component such as the obstacle detection unit 75 and the self-position estimation unit 77, and is mainly controlled by a microcomputer consisting of a CPU, a ROM, a RAM, an I/O controller, a timer, and the like. Realized.
The CPU organically operates various hardware based on a control program pre-stored in a ROM or the like, and executes a communication function, a self-position estimation function, and the like of the automatic guided vehicle AGV.
Further, as described above, in the automatic guided vehicle AGV, the controller 71 controls the rotational speed and traveling direction of the wheels based on the travel instruction signal transmitted from the travel management device SV.

The encoder 73 is a member attached to the two wheels (left wheel A1, right wheel A2) shown in FIG. It is to measure. The measured wheel rotation speed is given to the AGV movement amount calculator 72 .

The AGV movement amount calculation unit 72 corresponds to the movement amount calculation unit 47 described above, and is a part that calculates the cumulative amount of movement from the initial position at which the automatic guided vehicle AGV is started.
Using the measured number of rotations of the wheels, the cumulative amount of movement from the initial position is calculated. This cumulative movement amount corresponds to the second cumulative movement amount described above.
The initial position when the automatic guided vehicle AGV is activated corresponds to the stationary position before activation, and is represented by the position coordinates (X coordinate, Y coordinate) with the reference point of the map showing the travel area as the origin. , The position coordinates of this initial position on the map are stored in advance, or are set by the SV operator after startup.

Similar to the cumulative movement amount of manned vehicles MV, the accumulated movement amount is the distance (movement distance) moved from the position coordinates of the initial position where the automatic guided vehicle AGV was started, and the amount of angular change from the initial orientation at the initial position. For example, the running speed and direction measured at regular time intervals are stored as a history.
The route from the initial position to the current position can be identified from the history of travel speed and direction, and the position coordinates and travel direction (vehicle direction) of the current position of the automatic guided vehicle AGV can be determined from the position coordinates of the initial position and the cumulative amount of movement. is required.
Further, the calculated cumulative movement amount is given to self-position estimation section 77 as cumulative movement amount information 102 .

The laser light receiving unit 74 is a part that receives laser light emitted from the LiDAR installed on the manned guided vehicle MV.
The laser light receiving unit 74 is arranged in front of the housing of the automatic guided vehicle AGV so that the laser light coming from the traveling direction of the automatic guided vehicle AGV can be directly received.
In addition, the laser light receiving unit 74 is arranged so that the height from the ground of the laser light receiving unit 74 installed on the automatic guided vehicle AGV is approximately the same as the height from the ground of the LiDAR installed on the manned guided vehicle MV. Install.
The laser light receiving unit 74 receives the laser light emitted from the LiDAR of the manned vehicle MV, and when the received light intensity exceeds a predetermined value, it is determined that the manned vehicle MV is approaching.

When it determines that the manned vehicle MV is approaching, the automatic guided vehicle AGV stops autonomous driving or retreats to a position that does not interfere with the movement of the manned vehicle MV, thereby avoiding a collision.
However, if there is no need to directly receive the laser beam emitted from the LiDAR of the manned guided vehicle MV, the laser light receiving unit 74 may be omitted.

Similar to the obstacle detection unit 48 of the manned vehicle MV, the obstacle detection unit 75 measures distance measurement information (second distance measurement information) to obstacles existing in the traveling direction of the automatic guided vehicle AGV. , is a device that detects the position of an obstacle, and uses a LiDAR that emits laser light.
Distance information 103 to the obstacle is measured by LiDAR, and the obstacle is detected from the distance information. The distance measurement information 103 and the information on the detected obstacles are provided to the self-position estimation section 77 .
The obstacle detection section 75 corresponds to the second obstacle detection section described above.

In addition, the distance to the obstacle and the shape of the obstacle can be obtained from the distance measurement information from the LiDAR. You can get the approximate position coordinates on the map of the current position of the AGV.

The wireless communication unit 76 is a part that communicates information via the network 4, and performs data communication with the travel management device SV and the manned guided vehicle MV.
Since the automatic guided vehicle AGV is a vehicle that moves in a predetermined area, it communicates data wirelessly.
For example, it receives current position information broadcast from the manned guided vehicle MV, and receives a travel instruction signal and a stop signal sent from the travel management device SV.
Also, the current position information of the automatic guided vehicle AGV is transmitted to the travel management device SV.

The form of wireless communication of the unmanned guided vehicle AGV is preferably capable of wireless communication between relatively long-distance devices in order to communicate with the travel management device SV.
However, similar to the form of wireless communication of the manned vehicle MV, close proximity wireless communication such as Bluetooth or infrared communication may be used for communication between the manned vehicle MV and the automatic guided vehicle AGV.
As a result, data such as positional information can be reliably transmitted between the manned guided vehicle MV and the unmanned guided vehicle AGV in the vicinity even when the wireless communication connection is poor.

In addition, as the wireless communication function of the automatic guided vehicle AGV, it is equipped with both a long-distance wireless communication function and a short-range wireless communication function such as close proximity wireless communication. Using the function, information is sent infrequently, and information is sent frequently to nearby manned guided vehicles MV and unmanned guided vehicles AGV using short-range wireless communication functions. may

The self-position estimation unit 77 is a part that estimates the current position on the map where the automatic guided vehicle AGV exists, like the self-position estimation unit 49 of the manned guided vehicle MV.
The map information of the space area where the unmanned guided vehicle AGV travels, the cumulative movement amount calculated by the AGV movement amount calculation unit 72, the distance measurement information measured by the obstacle detection unit (LiDAR) 75, and the detected The current position of the automatic guided vehicle AGV is estimated from the information on the position of the obstacle (for example, the position coordinates of the obstacle on the map), and the current position on the map of the spatial area and the direction of travel Get information.
The self-position estimating section 77 corresponds to the second self-position estimating section described above.

The acquired information about the current position of the automatic guided vehicle AGV on the map includes the position coordinates (X coordinate, Y coordinate) of the current position of the automatic guided vehicle AGV and the traveling direction (body direction).
Information consisting of the position coordinates (X coordinate, Y coordinate) of the current position and the traveling direction (vehicle direction) is called AGV current position information 104 . AGV current position information 104 is stored in the storage unit 100 .
The acquired AGV current position information 104 of the automatic guided vehicle AGV is given to the self-position information transmission unit 78 .

Similarly, in the automatic guided vehicle AGV, the position coordinates of the current position on the map of the automatic guided vehicle AGV obtained from the accumulated movement amount calculated from the wheel rotation speed, and the current position on the map obtained by the obstacle detection unit 75 By estimating the current position of the automatic guided vehicle AGV using the position coordinates of can be done.

The self-position information transmission unit 78 is a part that transmits information (AGV current position information 104) regarding the current position of the automatic guided vehicle AGV on the map to the travel management device SV.
The AGV current position information 104 of the automatic guided vehicle AGV consists of the position coordinates (X coordinate, Y coordinate) of the current position of the automatic guided vehicle AGV and the traveling direction (body direction). From the AGV current position information, it is possible to know the position of the automatic guided vehicle AGV on the map of the traveling area and the traveling direction.

The AGV current position information of the unmanned guided vehicle AGV is transmitted by designating the travel management device SV as the transmission destination.
The travel management device SV that receives the AGV current position information of the automatic guided vehicle AGV, for example, uses the received AGV current position information to control the traveling of the automatic guided vehicle AGV so that the vehicles do not collide with each other. Send warning information to the manned guided vehicle MV.

The MV positional information acquisition unit 79 is a part that acquires the current positional information 66 transmitted from the manned guided vehicle MV by wireless communication by broadcasting.
The acquired current position information 66 is stored in the storage unit 100 as the MV position information 106 .
The MV position information 106 is information including the position coordinates of the center of gravity of the manned guided vehicle MV and the traveling direction (vehicle orientation), and is also called forklift posture information.
If the MV position information 106 is represented by position coordinates on a map, the map coordinates are as shown in FIG. 18, for example.
In the map coordinates of FIG. 18, the position of the center of gravity of the manned guided vehicle MV is indicated by the MV center of gravity (X01, Y01), and the traveling direction (body direction) of the manned guided vehicle MV is indicated by an arrow.
The MV position information 106 is given to the point group information generation unit 80 .

The point cloud information generation unit 80 is a part that generates point cloud information that reflects the shape of the manned guided vehicle MV, and also generates point cloud information that indicates the positions of objects detected as obstacles by the automatic guided vehicle AGV. This is the part to generate.

For example, as will be described later, from the MV position information 106, which is the current position information of the manned guided vehicle acquired from the manned guided vehicle MV, and the MV shape information 112, which indicates the outer shape of the manned guided vehicle by point cloud information, Generate MV point cloud information 107 that indicates the current attitude of the manned guided vehicle.
In addition, from the distance measurement information 103 from the obstacle detection unit 75 and the AGV current position information 104 consisting of information on the current position and traveling direction of the automatic guided vehicle estimated by the second self-position estimation unit 77, the automatic guided vehicle Point group information (AGV point group information 105) indicating the existence positions of objects detected as obstacles in the AGV is generated.

It is assumed that the shape of the manned vehicle MV is determined in advance, and information regarding the shape of the manned vehicle MV is stored in advance as MV shape information 112 in the storage unit 100 of the automatic guided vehicle AGV.
FIG. 19 shows an example of the MV shape information 112. As shown in FIG.
In FIG. 19, the outer shape of the manned vehicle MV is shown by point cloud information, and the vertical length of the manned vehicle MV is Wy, the horizontal length is Wx, and the manned vehicle MV The position of the center of gravity of is also shown. The traveling direction of the manned guided vehicle MV is the upward direction in FIG.

Since the MV position information 106 includes the positional coordinates and direction of the center of gravity of the manned guided vehicle MV, by superimposing the MV position information 106 and the MV shape information 112 specifying the shape of the manned guided vehicle MV, The posture (orientation) of the manned guided vehicle MV on the map can be specified.
By superimposing the MV position information 106 and the MV shape information 112, point cloud information of the manned guided vehicle MV is generated.
The point cloud information of the manned guided vehicle MV generated from the MV position information 106 is called MV point cloud information 107 .

FIG. 20 shows an explanatory diagram of an embodiment in which the MV position information 106 of FIG. 18 and the MV shape information 112 of FIG. 19 are superimposed.
In the MV position information 106 of FIG. 18, the traveling direction (vehicle direction) of the manned guided vehicle MV is tilted toward the upper left. Therefore, the MV shape information 112 of FIG. The MV position information 106 and the MV shape information 112 are superimposed so that the positions match.
MV point group information 107 indicating the current posture of the manned guided vehicle MV is obtained by extracting the point group information of the MV shape information 112 from the superimposed information in FIG.

FIG. 21 shows MV point group information 107 indicating the current posture of this manned guided vehicle MV.
If the manned guided vehicle MV is a forklift, the map coordinates shown in FIGS. running.

The point cloud information of the manned guided vehicle MV is also information that indicates the outer shape of the manned guided vehicle MV. I know the direction.
The MV point cloud information 107 is provided to a point cloud synthesizing unit 82 or a point cloud information comparing unit 83, which will be described later.

On the other hand, point group information indicating the existence position of an object detected as an obstacle in the automatic guided vehicle AGV and generated from the AGV current position information 104 and the distance measurement information 103 is called AGV point group information 105 .
FIG. 22 shows an explanatory diagram of an embodiment of the AGV ranging information 103. As shown in FIG.
The ranging information 103 is obtained by scanning a predetermined LiDAR measurement range with laser light emitted from the LiDAR of the AGV.
When an obstacle exists in a predetermined LiDAR measurement range, the distance measurement information 103 is acquired by receiving the laser light reflected from the obstacle, and the distance from the automatic guided vehicle AGV to the obstacle can be measured. It is possible to measure the position of obstacles relative to the vehicle AGV.

As shown in FIG. 22, the AGV ranging information 103 is acquired as information (point group information) from a plurality of points.
Assuming that the object existing in the LiDAR measurement range is a manned guided vehicle MV, as shown in Fig. 22, the AGV measurement is performed by the laser light reflected from a part of the outer shape of the manned guided vehicle MV on the side closer to the AGV. Distance information 103 is obtained.

FIG. 23 shows an example of AGV current position information 104 indicating the current position of the automatic guided vehicle AGV in map coordinates acquired from the self-position estimation unit 77 of the automatic guided vehicle AGV.
AGV point group information 105 is acquired by superimposing the AGV ranging information 103 in FIG. 22 and the AGV current position information 104 in FIG.

FIG. 24 shows AGV point group information 105 in which the AGV ranging information 103 of FIG. 22 and the AGV current position information 104 of FIG. 23 are superimposed.
From the AGV distance measurement information 103 in FIG. 22, the relative existence position of the obstacle seen from the automatic guided vehicle AGV is known, so the AGV distance measurement information 103 is superimposed on the AGV current position information 104 in FIG. , the map coordinates of the AGV ranging information 103 can be obtained.
The AGV point cloud information 105 is given to the point cloud synthesizing unit 82 or the point cloud information selecting unit 81, which will be described later.

The point cloud information selection unit 81 is a part that selects the point cloud information in the vicinity of the current position where the manned guided vehicle MV exists from the AGV point cloud information 105 .
For example, as will be described later, the AGV point cloud information 105 and the MV position information 106 are superimposed on the map of the spatial domain, and the point cloud near the current position where the manned guided vehicle exists among the AGV point cloud information 105 Select information to generate MV location selection information.
The selected AGV point group information is called MV position selection information 106a.
The AGV point cloud information 105 is information indicating the positions of objects detected as obstacles in the automated guided vehicle AGV. May contain objects.

Therefore, since the AGV point group information 105 may contain many objects, it is unclear from the AGV point group information 105 alone which part of the point group information corresponds to the manned guided vehicle MV.
Therefore, in order to specify the point group information corresponding to the manned vehicle MV from the AGV point group information 105, the MV position information 106 indicating the current position of the manned vehicle MV is used.
That is, the point group information selection unit 81 uses the AGV point group information 105 and the MV position information 106 to generate the MV position selection information 106a.

For example, as shown in FIG. 27 to be described later, the AGV point group information 105 of map coordinates shown in FIG. 26 and the MV position information 106 of map coordinates shown in FIG. 18 are superimposed.
In the superimposed information, the portion of the AGV point cloud information 105 belonging to the area within a predetermined radius around the center of gravity of the manned guided vehicle MV included in the MV position information 106 is represented by the map coordinates shown in FIG. , as MV position selection information 106a.
As a result, a portion (MV position selection information 106a) of the AGV point group information 105 corresponding to the MV position information 106 including the current position (the position of the center of gravity of the MV) where the manned guided vehicle MV is present is selected.
The MV position selection information 106 a is given to the point group information comparison section 83 .

In addition, by narrowing down the point cloud information used for comparison processing (matching calculation) performed by the point cloud information comparison unit 83 to be described later to the vicinity of the current position where the manned guided vehicle MV exists, the entire AGV point cloud information 105 can be obtained. can reduce the amount of computation compared to performing the matching operation using
In addition, since comparison processing is performed using only the point cloud information around the current position where the manned guided vehicle MV exists, even if the number of points that make up the point cloud information is insufficient, the position of the MV can be moved to an unrelated location. It is possible to accurately calculate the positional relationship between the point cloud information of AGV and MV.

The point cloud synthesizing unit 82 synthesizes the MV point cloud information 107 generated by the point cloud information generating unit 80 and the AGV point cloud information 105, and generates obstacle information 108 including the current position of the manned guided vehicle MV. This is the part to do.
This obstacle information 108 is, for example, information as shown in FIG. 25, and corresponds to MV position coordinate information including the position coordinates of the current position of the manned guided vehicle MV.
Obstacle information 108 in FIG. 25 is a combination of MV point group information 107 in FIG. 21 and AGV point group information 105 in FIG.

The obstacle information 108 includes point cloud information (MV point cloud information 107 ) of the current position of the manned guided vehicle MV, and further includes AGV current position information 104 included in the AGV point cloud information 105 .
The obstacle information 108 is stored in the storage unit 100 of the automatic guided vehicle AGV and used to determine the distance between the automatic guided vehicle AGV and the manned guided vehicle MV.

Further, as will be described later, when correcting the MV point cloud information 107, the point cloud synthesizing unit 82 synthesizes the MV point cloud correction information 109 generated by the point cloud information comparing unit 83 and the AGV point cloud information 105. , generates obstacle information 108 .
In this case, for example, obstacle information 108 is generated by synthesizing MV point group correction information 109 and AGV point group information 105, as shown in FIG.

The point cloud information comparison unit 83 is a portion that compares the MV point cloud information 107 with the MV position selection information 106a selected by the point cloud information selection unit 81. By this comparison, the MV point cloud information 107 indicates MV point group correction information 109 is generated by correcting the current attitude of the manned guided vehicle.
The point group information comparison unit 83 is also called a matching unit.

The matching method used in this correction can use what is called an ICP (Iterative Closest Point) algorithm.
Using this matching method, for example, using the position coordinates of the manned guided vehicle MV (MV position information), AGV point cloud information within a predetermined distance from the center of gravity of the MV is extracted, and the ICP algorithm is applied to this. , corrects the MV point cloud information 107 of the manned guided vehicle MV so as to best match the obstacle detection result detected by the LiDAR.

In general, self-positions estimated in AGVs and MVs contain errors.
Also, the time at which the manned guided vehicle MV transmits the coordinate information of its own position is different from the generation time of the point cloud information generated from the ranging information measured by the obstacle detector (LiDAR) of the automated guided vehicle AGV. .
Therefore, between the MV point cloud information 107 generated from the MV position information 106 acquired from the manned guided vehicle MV and the AGV point cloud information 105 generated from the distance measurement information 103 actually measured by the LiDAR of the unmanned guided vehicle AGV there is a discrepancy.
Especially when the manned guided vehicle MV is moving, the deviation becomes large.
Therefore, by correcting the MV point group information 107, it is possible to improve the accuracy of the information on the current position and traveling direction of the manned guided vehicle MV.

The point cloud information comparison unit 83 of the present invention uses the MV point cloud information 107 and the MV position selection information 106a as shown in FIG. MV point cloud correction information 109 is generated by correcting the MV point cloud information 107 in consideration of the point cloud deviation amount (point cloud deviation amount 110).

For example, as shown in FIG. 29, the MV point cloud information 107 in FIG. 21 and the MV position selection information 106a in FIG. ) is calculated.
The MV point group information 107 represents the contour shape of the MV.
The MV position selection information 106a indicates a part of the contour of the MV detected as an obstacle.

In FIG. 29, as the amount of point cloud deviation between the MV point group information 107 and the MV position selection information 106a, the deviation in the X-axis direction and the deviation in the Y-axis direction are calculated. In general, not only the translation deviation but also the rotation deviation occurs, but for the sake of simplicity of explanation, it is assumed that only the translation deviation occurs here. The ICP algorithm can calculate translational and rotational displacements at once.
Here, the deviation in the X-axis direction is X21-X11, and the deviation in the Y-axis direction is Y21-Y11.
The deviation in the X-axis direction and the deviation in the Y-axis direction are stored as the point cloud deviation amount 110 , given to the MV position corrector 84 , and used to correct the MV position information 106 .

Also, as in FIG. 29, when the MV point group information 107 and the MV position selection information 106a are deviated, the position of the MV point group information 107 is corrected.
For example, the MV point cloud information 107 is moved downward by the point cloud shift amount so as to overlap the MV position selection information 106a.
FIG. 30 shows the state after the MV point cloud information 107 is moved by the point cloud deviation amount so as to overlap with the MV position selection information 106a.
As shown in FIG. 30, the MV point group correction information 109 is the MV point group information 107 after being moved by the point group deviation amount.
The MV point cloud correction information 109 is given to the point cloud synthesizing unit 82 .

The MV position correction unit 84 is a part that corrects the MV position information 106 using the point cloud deviation amount 110 .
The corrected MV position information is MV corrected position information 111 and is stored in the storage unit 100 .
As described above, when the MV point cloud information 107 is moved downward by the point cloud deviation amount so as to overlap the MV position selection information 106a, the MV correction position information 111 is the MV position on the same map coordinates. It becomes the same position as the selection information 106a.
For example, as shown in FIG. 32, the center-of-gravity position of the MV position information 106 (MV center-of-gravity: X01, Y01) is obtained by using the point cloud deviation amount 110 to obtain the center-of-gravity position of the MV correction position information 111 (MV center of gravity: X02, Y01). Y02).

The vehicle approach determination unit 85 corresponds to the above-described second vehicle approach determination unit, calculates the distance between the own AGV and other vehicles, and determines whether another vehicle is nearby or the other vehicle is closer to the own vehicle. This is the part that determines whether or not the vehicle (AGV) is approaching.
Using the MV position information 106 obtained from the MV as described above and the AGV current position information 104, the distance between the vehicle (inter-vehicle distance LA1) between the own AGV and the MV is calculated, and the inter-vehicle distance LA1 is compared with distance information (unconditional stopping distance L0, etc.) preset and stored in the storage unit 100 to determine whether the vehicle is approaching or the like.

Depending on the determined approaching state, subsequent operation of the own AGV, such as whether to stop the own AGV, continue normal running, or decelerate, is determined.
An example of vehicle approach determination and travel control processing in this automatic guided vehicle AGV will be described later.

The attribute information addition unit 86 is a part that adds attribute information regarding the MV to the MV position information 106 and the MV point group information 107 .
As described above, the AGV can acquire the MV position information 106 by receiving the current position information 66 transmitted from the MV.
If the current location information 66 transmitted from the MV contains information (MV attribute information) about the operating state of the MV, the AGV adds the MV attribute information to the acquired MV location information 106. , the vehicle-to-vehicle distance between the AGV and the MV as well as the MV attribute information is used to determine the current operating state of the MV and control the AGV's own running.

In MV, it is possible to acquire information about the current operating state of the vehicle and the operating state of the driver from the steering wheel operation and the rotational speed of the wheels.
For example, if the MV's steering wheel is always rotating or the rotation speed is not zero, we can get the information that it is currently "driving", and if the rotation speed is zero, it is "stopping". information can be obtained.

Therefore, in the MV, it is currently "driving", "stopping", "driver is on board", "carrying luggage", and "loading and unloading luggage". Acquire information about the MV's own operating state, such as the fact that it exists, as MV attribute information.
Then, the MV broadcasts the current position information 66 by adding the acquired information (MV attribute information) about its own operating state to the current position information 66 .
Thereby, the AGV can acquire the MV attribute information added to the current location information 66 of the MV.

That is, the AGV can determine whether the MV is currently operating or currently stopped by acquiring the MV attribute information.
For example, if the acquired MV attribute information indicates that the MV is currently driving, the AGV can pause driving and wait for the MV to pass.
In addition, if the acquired MV attribute information indicates that the MV is currently stopped, the AGV performs actions to avoid collision with the MV, for example, considers the MV as an obstacle and avoids the obstacle. You can run to run.
Thus, the AGV can control its own running by using the MV attribute information acquired from the MV.

The request information acquisition unit 87 is a part that acquires request information transmitted from the travel management device SV.
For example, it acquires travel route information, travel condition (speed, direction) information, travel start request, travel stop request, charge request, etc., sent from the SV.

The travel stop portion 88 is a portion for stopping the self travel of the automatic guided vehicle AGV.
For example, it stops running when it receives a request to stop running from the SV.
Further, when the vehicle approach determination unit 85 determines that the manned guided vehicle MV within a predetermined distance has approached, the automatic guided vehicle AGV stops running.

The storage unit 100 is a part that stores information and programs necessary for executing each function of the automatic guided vehicle AGV, and includes semiconductor storage elements such as ROM, RAM, and flash memory, storage devices such as HDD and SSD, and other storage devices. of storage media are used.
For example, the storage unit 100 stores map information 101, cumulative movement amount information 102, ranging information 103, AGV current position information 104, AGV point group information 105, MV position information 106, MV point group information 107, obstacle information 108, and so on. , MV point group correction information 109, point group shift amount 110, MV correction position information 111, MV shape information 112, and the like are stored.

The map information 101 is information of the spatial area in which the automatic guided vehicle AGV travels, and as described above, is the same information as the map information stored in the travel management device SV.
The automatic guided vehicle AGV uses this map information 101 to autonomously travel and estimate its own current position.

The accumulated movement amount information 102 is information calculated by the AGV movement amount calculation unit 72 as described above, and includes the distance (movement distance) moved from the position coordinates of the initial position of the automatic guided vehicle AGV and the initial and the amount of change in angle from the azimuth.
The ranging information 103 is information acquired from the LiDAR and is information indicating the distance to the obstacle. The ranging information 103 is, for example, AGV ranging information as shown in FIG.

As described above, the AGV current position information 104 is information about the current position of the automatic guided vehicle AGV on the map acquired by the self-position estimation unit 77, and includes the position coordinates (X coordinate, Y coordinate) of the current position, It consists of a running direction (vehicle direction). The AGV current position information 104 is, for example, information as shown in FIG.

The AGV point cloud information 105 is information generated by the point cloud information generating unit 80 as described above, and is point cloud information indicating the existence position of an object detected as an obstacle in the automatic guided vehicle AGV. The AGV point group information 105 is, for example, information as shown in FIG.

The MV position information 106 is information obtained by the MV position information obtaining unit 79, as described above, and corresponds to the current position information 66 transmitted from the manned guided vehicle MV. and the direction of travel (body direction) (forklift posture information). The MV position information 106 is, for example, information as shown in FIG.

The MV point cloud information 107 is information generated by the point cloud information generation unit 80 as described above, and is the current state of the manned guided vehicle MV generated by superimposing the MV position information 106 and the MV shape information 112. It is point cloud information indicating the posture of The MV point group information 107 is information as shown in FIG. 21, for example.

The obstacle information 108 is information generated by the point group synthesizing unit 82 as described above, and corresponds to MV position coordinate information including the position coordinates of the current position of the manned guided vehicle MV. Obstacle information 108 is information as shown in FIG. 25, for example.

The MV point cloud correction information 109 is information generated by the point cloud information comparison unit 83, as described above, and is the amount of deviation (point cloud deviation amount 110) between the MV point cloud information 107 and the MV position selection information 106a. It corresponds to the MV point group information 107 corrected by using.
The MV point group correction information 109 is information as shown in FIG. 30, for example.

The point cloud deviation amount 110 is information generated by the point cloud information comparison unit 83, as described above, and corresponds to the deviation amount between the MV point cloud information 107 and the MV position selection information 106a. and the MV position selection information 106a are superimposed on the map coordinates. The point group deviation amount 110 is information as shown in FIG. 29, for example.

The MV corrected position information 111 is information generated by the MV position correction unit 84 as described above, and is information obtained by correcting the MV position information 106 using the point cloud shift amount 110 . The point group deviation amount 110 is information as shown in FIG. 32, for example.

The MV shape information 112 is information about the shape of the manned vehicle MV, and is stored in advance in the storage unit 100 of the automatic guided vehicle AGV. The MV shape information 112 is, for example, information as shown in FIG.

<Example of vehicle travel control processing>
(Description of vehicle approach determination and travel control processing in the travel management device)
FIG. 12 shows a flowchart of an embodiment of vehicle approach determination and travel control processing in the travel management device.
Here, the process of controlling the travel of the AGV based on the vehicle approach determination executed by the travel management device SV and the inter-vehicle distance between the two vehicles will be described.

For example, as shown in Fig. 5, the positional information of all automatic guided vehicles AGV and all manned guided vehicles MV traveling in the warehouse area is acquired, and the distance between any two AGVs and MVs is acquired. Calculate the distance LA1 and determine whether the two vehicles are approaching each other.
In this embodiment, an unconditional stopping distance L0 and a conditional stopping distance L1 are preset and stored in the storage unit 30 of the SV as criteria for determining whether or not a vehicle is approaching.
The unconditional stopping distance L0 is a reference distance for stopping the AGV. When the vehicle-to-vehicle distance LA1 is shorter than the unconditional stopping distance L0 (LA1<L0), the AGV is stopped.

The conditional stopping distance L1 is a reference distance for determining whether the AGV is running normally or decelerating, and is set to a distance longer than the unconditional stopping distance L0 (L1>L0).
For example, when the vehicle-to-vehicle distance LA1 is equal to or greater than the conditional stopping distance L1 (LA1≧L1), the AGV is normally driven.
Alternatively, when the vehicle-to-vehicle distance LA1 is equal to or greater than the unconditional stopping distance L0 and shorter than the conditional stopping distance L1 (L0≦LA1<L1), the approaching state of the AGV and the MV determines whether the AGV travels.

In step S11 of FIG. 12, AGV current position information 104 is obtained from all automatic guided vehicles AGVs.

In step S12, MV position information 106 is obtained from all manned guided vehicles MV.
The AGV current position information 104 and the MV position information 106 contain the current position coordinates of the AGV and MV on the map, respectively. can be calculated.

In step S13, when the inter-vehicle distance LA1 between any two AGVs and MVs is stored in the previous calculation of the inter-vehicle distance, this previous inter-vehicle distance LA1 is stored in the saved distance LA2 (LA2 =LA1).
The saved distance LA2 is used to determine whether the two AGVs and MVs are approaching or separating.

In step S14, the inter-vehicle distance LA1 between each AGV and each MV is calculated from the position coordinates of all MVs and AGVs and stored.
In step S15, the calculated vehicle-to-vehicle distance LA1 is compared with the unconditional stopping distance L0 and the conditional stopping distance L1.

In step S16, the vehicle-to-vehicle distance LA1 is compared with the unconditional stopping distance L0. If the vehicle-to-vehicle distance LA1 is shorter than the unconditional stopping distance L0 (LA1<L0), the process proceeds to step S19; otherwise, step S17. proceed to

In step S17, the inter-vehicle distance LA1 and the conditional stopping distance L1 are compared, and if the inter-vehicle distance LA1 is greater than or equal to the unconditional stopping distance L0 and shorter than the conditional stopping distance L1 (L0≤LA1<L1), step Proceed to S18, otherwise (LA1≧L1), proceed to step S21.

In step S18, the current inter-vehicle distance LA1 is compared with the saved previous inter-vehicle distance LA2, and if LA1<LA2, the process proceeds to step S22, otherwise, the process proceeds to step S24.
Here, when LA1<LA2, the vehicle-to-vehicle distance LA1 between the AGV and MV is longer than the unconditional stopping distance L0 but shorter than the conditional stopping distance L1, and the AGV and MV are traveling in a direction approaching each other. It means that there is a possibility of collision.
When LA1≧LA2, the inter-vehicle distance LA1 between the AGV and MV is shorter than the conditional stopping distance L1. This means that the vehicle is traveling in a direction in which the two are moving away from each other (separate direction), and that there is little possibility of collision.

In step S19, since the inter-vehicle distance LA1 between the AGV and the MV is shorter than the unconditional stopping distance L0, the AGV and the MV are quite close to each other, and there is a high possibility of collision. stop the running AGV.
Here, a stop request is transmitted from the running management device SV to the AGV approaching the MV.
An AGV that receives a stop request stops at its current position.
Alternatively, if there is a shelter nearby, the AGV that receives the stop request may travel to that shelter and stop.

In step S20, warning information is sent to the MV approaching the AGV, indicating that there is a possibility of collision with the AGV, that there is an AGV nearby, and the like.
The MV that has received the warning information may, for example, display the warning information on the display screen of the MV, or notify the driver of the MV of the warning information by voice.

In step S21, since the inter-vehicle distance LA1 is greater than or equal to the conditional stopping distance L1, the AGV and the MV are not approaching each other, and the possibility of collision is considered to be low. Send.

In step S22, LA1<LA2, the AGV and the MV are traveling in the direction of approaching, and there is a possibility that the AGV and the MV will collide, so the traveling of the AGV that is approaching the MV is stopped. Here, a stop request is transmitted from the running management device SV to the AGV approaching the MV.
In step S23, similarly to step S20, warning information is sent to the MV approaching the AGV, indicating that there is a possibility of collision with the AGV, that there is an AGV nearby, and the like.

In step S24, the AGV and the MV are traveling while maintaining a constant distance, or the AGV and the MV are traveling in a direction in which they move away from each other (separation direction). Since the inter-vehicle distance LA1 between the AGV and the MV is shorter than the conditional stopping distance L1, deceleration processing is performed to slow down the AGV. That is, it transmits a deceleration request to the AGV.
After the AGV decelerates, the AGV and MV move further apart, and if the vehicle-to-vehicle distance LA1 between the AGV and MV becomes longer than the conditional stopping distance L1, an instruction to switch to normal driving is sent to the AGV. good too.

As described above, by controlling the travel of the AGV based on the inter-vehicle distance between the AGV and the MV, it is possible to ensure sufficient safety in the travel of the AGV and the MV.

(Description of vehicle approach determination and travel control processing in an unmanned guided vehicle)
FIG. 13 shows a flowchart of an embodiment of vehicle approach determination and travel control processing in an automatic guided vehicle.
Here, the process of controlling the travel of the own AGV based on the vehicle approach determination executed by the automatic guided vehicle AGV and the inter-vehicle distance between the two vehicles will be described.

For example, from all the manned guided vehicles MV traveling in the warehouse area as shown in Fig. 5, each position information is acquired, the distance LA1 between the own AGV and each MV is calculated, and each MV is approaching its own AGV.
In this embodiment, unconditional stopping distance L0 and conditional stopping distance L1 are preset and stored in the storage unit 100 of the AGV as the criteria for determining whether the MV is approaching, as in FIG. It shall be.

In step S31 of FIG. 13, the AGV current position information 104 is obtained from its own automatic guided vehicle AGV.
In step S32, MV position information 106 is acquired from all manned guided vehicles MV, as in step S12 described above.
This MV location information 106 corresponds to broadcasted information.

In step S33, similarly to step S13 described above, if the previous inter-vehicle distance calculation has stored the inter-vehicle distance LA1 between own AGV and MV, the previous inter-vehicle distance LA1 is stored as the stored distance. Save to LA2 (LA2=LA1).

In step S34, from the position coordinates of all the MVs and the own AGV, the inter-vehicle distance LA1 between the own AGV and each MV is calculated and stored.
In step S35, the calculated vehicle-to-vehicle distance LA1 is compared with the unconditional stopping distance L0 and the conditional stopping distance L1.

In step S36, the vehicle-to-vehicle distance LA1 is compared with the unconditional stopping distance L0, and if the vehicle-to-vehicle distance LA1 is shorter than the unconditional stopping distance L0 (LA1<L0), the process proceeds to step S39; otherwise, step S37. proceed to

In step S37, the inter-vehicle distance LA1 and the conditional stopping distance L1 are compared, and if the inter-vehicle distance LA1 is greater than or equal to the unconditional stopping distance L0 and shorter than the conditional stopping distance L1 (L0≤LA1<L1), step Proceed to S38, otherwise (LA1≧L1), proceed to step S40.

In step S38, the current inter-vehicle distance LA1 is compared with the saved previous inter-vehicle distance LA2, and if LA1<LA2, the process proceeds to step S41, otherwise, the process proceeds to step S42.

In step S39, since the vehicle-to-vehicle distance LA1 between the own AGV and MV is shorter than the unconditional stopping distance L0, the AGV and MV are quite close to each other, and it is considered highly likely that they will collide. , stop its own running. An AGV that has stopped traveling may transmit information about the fact that it has stopped and the position at which it has stopped to the travel management device SV.
Alternatively, if there is a shelter nearby, the AGV may travel to that shelter and stop.
Also, the AGV may send warning information to MVs approaching the AGV indicating that there is a possibility of colliding with the AGV, that there is an AGV nearby, and the like.
In addition, the AGV may be equipped with a speaker and a warning light to warn nearby MVs of danger by sound or lighting of the warning light.

In step S40, the inter-vehicle distance LA1 is greater than or equal to the conditional stopping distance L1, so the AGV and the MV are not approaching each other, and it is considered unlikely that they will collide.

In step S41, LA1<LA2, the AGV and the MV are traveling in a direction approaching each other, and there is a possibility that the AGV and the MV will collide, so the own AGV stops traveling.
In this case as well, the MV that is approaching the AGV will be sent warning information indicating that there is a possibility of colliding with the AGV and that there is an AGV nearby. You may warn nearby MVs of the danger with a voice or the lighting of a warning light.

In step S42, the AGV and the MV are traveling while maintaining a constant distance, or the AGV and the MV are traveling in a direction in which they move away (separate direction), so the possibility of collision is small, but the AGV Since the inter-vehicle distance LA1 between the AGV and the MV is shorter than the conditional stopping distance L1, the travel speed of the own AGV is reduced in the same manner as in step S24.
Even at this time, the AGV is equipped with a speaker and a warning light, and it is possible to call attention to nearby MVs with sound and lighting of the warning light.
Also, after the AGV decelerates, the AGV and the MV move further apart, and if the vehicle-to-vehicle distance LA1 between the AGV and the MV becomes longer than the conditional stopping distance L1, the driving of the own AGV can be switched to normal driving. good.

As described above, by acquiring the MV position information 106 broadcast from the MV and controlling the traveling of the own AGV according to the inter-vehicle distance between the own AGV and the MV, the traveling of the AGV and the MV is sufficiently safe. can ensure the integrity of the
Also, although not shown in FIG. 13, if the MV position information 106 acquired from the manned guided vehicle MV contains information (MV attribute information) regarding the MV's own operation state, this MV attribute information is used. Then, the running state of the MV may be determined and the running of the own AGV may be controlled. As a result, it is possible to accurately control the running of the own AGV while considering safety, and to ensure safer running of the AGV and MV.

<Description of Self-Position Estimation Processing of Automated Guided Vehicles>
FIG. 15 shows a configuration block diagram of an embodiment related to self-position estimation processing of an automatic guided vehicle AGV.
The automatic guided vehicle AGV, as already explained with reference to FIG. 10, is provided with an encoder 73 that measures the respective rotation speeds of the left wheel A1 and the right wheel A2.
The wheel rotation speeds of the left wheel A1 and the right wheel A2 are output to the AGV movement amount calculator 72 from the encoders 73 attached to the left wheel A1 and the right wheel A2.

The AGV movement amount calculation unit 72 calculates cumulative movement amount information 102 using the two input wheel rotation speeds, and provides the information to the self-position estimation unit 77 .
The cumulative movement amount information 102 is information that includes the distance (movement distance) that the automatic guided vehicle AGV has moved from the position coordinates of the initial position and the amount of angular change from the initial orientation at the initial position.

On the other hand, when the LiDAR corresponding to the obstacle detection unit 75 detects an obstacle, the LiDAR provides the distance measurement information 103 to the self-position estimation unit 77 .

The self-position estimation unit 77 refers to the map information 101 stored in the storage unit 100, corrects the accumulated movement amount information 102 using the accumulated movement amount information 102 and the distance measurement information 103, and corrects the accumulated movement amount information 102. AGV current position information (AGV current position information 104) is generated.

The AGV current position information 104 of the automatic guided vehicle AGV is transmitted to the network 4 by the self-position information transmission unit 78 .
When the transmission destination is set to the running management device SV, the AGV current position information 104 is transmitted only to the running management device SV.
However, the AGV current position information 104 may be broadcast without setting the destination. In this case, the travel management device SV, the manned guided vehicle MV, and the other unmanned guided vehicle AGV connected to the network 4 can receive the AGV current position information 104 .

<Description of obstacle information generation processing for automated guided vehicles>
(Obstacle information generation processing: Example 1)
FIG. 16 shows a configuration block diagram of an embodiment related to the obstacle information generation processing of the automatic guided vehicle AGV.
FIG. 4 shows the functional configuration of the automatic guided vehicle AGV, and FIG. 16 is a block diagram showing the relationship of each element of these functional configurations.

As described above, when the current position information 66 broadcast from the manned guided vehicle MV to the network 4 is received by the automatic guided vehicle AGV, the MV position information 106 corresponding to the current position information 66 is obtained from the MV position information acquisition unit 79. is provided to the point cloud information generation unit 80 .
The MV position information 106 is information as shown in FIG. 18 described above.

A point cloud information generation unit 80 generates MV point cloud information 107 from MV position information 106 and MV shape information 112 stored in advance.
The MV shape information 112 is information as shown in FIG. 19 described above.
The MV point group information 107 is information as shown in FIG.

On the other hand, when an obstacle is detected by the LiDAR corresponding to the obstacle detection unit 75 , the LiDAR provides the distance measurement information 103 to the point group information generation unit 80 .
The distance measurement information 103 is information as shown in FIG. 22 described above.
Also, the AGV current position information 104 output from the self-position estimation unit 77 described above is given to the point cloud information generation unit 80 .
The AGV current position information 104 is information as shown in FIG. 23 described above.

The point cloud information generator 80 uses the distance measurement information 103 and the AGV current position information 104 to generate AGV point cloud information 105 .
The AGV point group information 105 is information as shown in FIG.

The point group synthesis unit 82 synthesizes the MV point group information 107 and the AGV point group information 105 on map coordinates to generate obstacle information 108 .
The obstacle information 108 is information as shown in FIG. 25, and is information indicating the positional relationship between the AGV and the MV.
Obstacle information 108 is stored in the storage unit 100 of the AGV.

(Obstacle information generation processing: Example 2)
FIG. 17 shows a configuration block diagram of an embodiment related to the obstacle information generation processing of the automatic guided vehicle AGV.
FIG. 17 is also a block diagram showing the relationship of each element of the functional configuration of the automatic guided vehicle AGV shown in FIG. 4, similar to FIG.
However, unlike FIG. 16, it is a block diagram in the case of correcting the MV point group information 107 using the MV position selection information 106a.

16, when the current position information 66 broadcast from the manned guided vehicle MV to the network 4 is received by the automatic guided vehicle AGV, the MV position information corresponding to the current position information 66 is obtained from the MV position information acquisition unit 79. 106 is provided to the point cloud information generator 80 .
Also, the MV position information 106 is given to the point group information selection unit 81 and the MV position correction unit 84 .

A point cloud information generation unit 80 generates MV point cloud information 107 from MV position information 106 and MV shape information 112 stored in advance.
The MV point cloud information 107 is information as shown in FIG.

As in FIG. 16 , when an obstacle is detected by the LiDAR corresponding to the obstacle detection unit 75 , the distance measurement information 103 is given to the point cloud information generation unit 80 from the LiDAR.
Also, the AGV current position information 104 output from the self-position estimation unit 77 described above is given to the point cloud information generation unit 80 .

As in FIG. 16 , the point cloud information generator 80 uses the distance measurement information 103 and the AGV current position information 104 to generate the AGV point cloud information 105 .
The AGV point cloud information 105 is information as shown in FIG.

The point group information selection unit 81 selects the current position of the manned guided vehicle MV from the given AGV point group information 105 by using the MV position information 106 indicating the current position of the manned guided vehicle MV. Select point cloud information near .
As shown in FIG. 27, the MV position information 106 and the AGV point group information 105 are superimposed on map coordinates. , as the MV position selection information 106a.
The MV position selection information 106a, which is the AGV point group information selected by the point group information selection unit 81, is provided to the point group information comparison unit 83. FIG.
The MV position selection information 106a is information as shown in FIG. 28 described above.

The point cloud information comparison unit 83 compares the MV point cloud information 107 and the MV position selection information 106a, calculates the amount of deviation between the two (point cloud deviation amount 110), and uses this point cloud deviation amount 110 to , to correct the MV point cloud information 107 .
The point cloud deviation amount 110 is information as shown in FIG.
MV point cloud correction information 109 that is the corrected MV point cloud information 107 is generated by the point cloud information comparison unit 83 and supplied to the point cloud synthesizing unit 82 .
The MV point group correction information 109 is information as shown in FIG. 30 described above.

The point cloud synthesizing unit 82 synthesizes the MV point cloud correction information 109 and the AGV point cloud information 105 on map coordinates to generate obstacle information 108 .
The obstacle information 108 is information as shown in FIG. 31 described above.
Obstacle information 108 is stored in the storage unit 100 of the AGV.

The MV position correction unit 84 corrects the MV position information 106 using the point cloud deviation amount 110 . For example, as shown in FIG. 32 described above, MV corrected position information 111 obtained by correcting the MV position information 106 is generated and stored in the storage unit 100 of the AGV.

<Example of LiDAR for manned guided vehicle MV and unmanned guided vehicle AGV>
As mentioned above, the manned guided vehicle MV and the unmanned guided vehicle AGV are equipped with a LiDAR that corresponds to the obstacle detection unit. The height from the ground of the LiDAR installed is the same, or the height from the ground of the LiDAR installed on the manned vehicle MV is higher than the height from the ground of the LiDAR installed on the automated guided vehicle AGV It is preferable to make it high.

First, the ranging information measured by LiDAR is used for MV and AGV self-position estimation. From the viewpoint of achieving the same accuracy, it is preferable that the height of the LiDAR attached to the manned vehicle MV and the height of the LiDAR attached to the automatic guided vehicle AGV be the same.

However, it is also possible to make the height of the LiDAR attached to the manned guided vehicle MV and the height of the LiDAR attached to the automated guided vehicle AGV different.
FIG. 33 shows an explanatory diagram of an embodiment when a manned guided vehicle MV and an unmanned guided vehicle AGV with different LiDAR heights are viewed from the side.
FIG. 33 shows that the height Hm of the LiDAR 48 attached to the manned vehicle MV is made higher than the height Ha of the LiDAR 75 attached to the automatic guided vehicle AGV.
A forklift, which is a manned guided vehicle (MV), is usually higher than an unmanned guided vehicle (AGV).

In general, even if the height of the LiDAR is slightly increased or decreased, the placement of obstacles does not change significantly, and the accuracy of self-localization is not significantly affected.
However, when LiDARs installed at the same height come close to each other, the emitted laser beams may interfere and observe obstacles in places that do not exist.
A pseudo-obstacle that is erroneously observed in this way may lead to malfunction of travel control or obstacle avoidance.

In particular, it is possible to reduce the impact by controlling the movement of autonomously traveling AGVs so that they do not approach each other. and LiDAR interference can be a problem.
Therefore, by making the heights of the LiDARs attached to the MV and the AGV different, as shown in FIG.

Also, if the LiDAR of the manned guided vehicle MV is installed at a higher position than the LiDAR of the unmanned guided vehicle AGV, the LiDAR of the manned guided vehicle MV uses the LiDAR that can measure long distances rather than the LiDAR used in the AGV. It is possible to

In general, manned guided vehicles MV, which run at a higher speed than AGV, use LiDAR, which can measure distant obstacles, because short-range obstacles change rapidly, but distant walls and obstacles change slowly. This enables more stable self-position estimation.
Also, if the LiDAR is installed at a low position, it will detect the ground, which limits the range of the LiDAR.
Therefore, in the manned guided vehicle MV, the LiDAR, which is the obstacle detection unit 48, is installed at a higher position than the LiDAR of the AGV. This prevents it and enables stable self-localization.

<Example of automatic guided vehicle AGV equipped with a laser receiver>
FIG. 34 shows an explanatory diagram of an embodiment when a manned guided vehicle MV equipped with LiDAR and an unmanned guided vehicle AGV equipped with a laser light receiving section are viewed from the side.
Similarly to FIG. 33, FIG. 34 also shows that the height of the LiDAR 48 attached to the manned vehicle MV is higher than the height of the LiDAR 75 attached to the automatic guided vehicle AGV.
Further, in FIG. 34, the laser light receiving unit 74 is attached to the automatic guided vehicle AGV, and the height Hr at which the laser light receiving unit 74 is attached is substantially the same as the height Hm of the LiDAR 48 attached to the manned guided vehicle MV.

As described above, the laser light receiving unit 74 is installed to directly receive the laser light emitted from the LiDAR of the manned guided vehicle MV. In order to detect and not detect the laser light emitted from the LiDAR 75 of the automatic guided vehicle AGV attached at a low position, for example, the laser light receiving unit 74 can be arranged at a position as shown in FIG. preferable.

When it is determined that the manned guided vehicle MV is approaching by receiving the laser light emitted from the LiDAR of the manned guided vehicle MV by the laser light receiving unit 74, the unmanned guided vehicle AGV stops autonomous traveling, Alternatively, the collision is avoided by retreating to a position that does not interfere with the travel of the manned guided vehicle MV.

In this way, by detecting the laser light emitted from the LiDAR 48 of the manned vehicle MV, the approach of the manned vehicle MV can be directly observed in the automated guided vehicle AGV, and the automatic guided vehicle AGV and the travel management device can be used. Even when a communication failure occurs with the SV, it is possible to ensure a minimum level of safety.

1 travel management device,
2 manned vehicles,
3 automated guided vehicles,
4 networks,
5 shelves,
11 control unit,
12 operation unit,
13 display unit,
14 communication unit,
21 AGV position information acquisition unit,
22 MV position information acquisition unit,
23 vehicle approach determination unit,
24 AGV operation control unit,
25 warning notification unit;
30 storage unit,
31 map information,
32 AGV location information,
33 MV location information,
34 approaching vehicle information,
35 vehicle current position information,
41 control unit,
42 vehicle speed measurement unit,
43 vehicle speed encoder,
44 traveling direction measuring unit,
45 rotary angle encoder,
46 wireless communication unit,
47 movement amount calculation unit,
48 Obstacle detection unit (LiDAR),
49 self-position estimation unit,
50 self-location information transmission unit,
51 alert acquisition unit;
60 storage unit,
61 map information,
62 wheel speed,
63 steering wheel rotation angle,
64 cumulative movement amount information,
65 ranging information,
66 current location information,
71 control unit,
72 AGV movement amount calculation unit,
73 Encoder,
74 laser receiver,
75 obstacle detector (LiDAR),
76 wireless communication unit,
77 self-position estimation unit,
78 self-location information transmission unit,
79 MV position information acquisition unit,
80 point cloud information generator,
81 point cloud information selection unit,
82 point group synthesizing unit,
83 point cloud information comparison unit,
84 MV position corrector,
85 vehicle approach determination unit,
86 attribute information addition unit,
87 request information acquisition unit,
88 travel stop,
100 storage unit,
101 map information;
102 cumulative movement amount information;
103 ranging information;
104 AGV current position information,
105 AGV point cloud information,
106 MV location information,
107 MV point cloud information,
108 obstacle information;
109 MV point cloud correction information,
110 point cloud shift amount,
111 MV correction position information,
112 MV shape information,
F1 headlamps,
F2 flasher lamp,
F3 mast,
F4 backrest,
F5 fork,
F6 road wheel,
F7 head guard,
F8 handle,
F9 inspection cover,
F10 battery,
F11 brake pedal,
F12 wheels,
F13 caster wheel,
A1 left wheel,
A2 right wheel,
A3 Caster,
A4 motor

Claims (6)

A vehicle driving management system in which a manned vehicle and an unmanned vehicle capable of autonomous driving are connected via a network,
The distance traveled from the initial position when the unmanned vehicle is started, which is calculated using the map information of the space area in which the unmanned vehicle travels, which is stored in advance, and the measured number of rotations of the wheels, and the distance from the initial azimuth at the initial position. estimating information about the current position and traveling direction of the robot on the map of the spatial area by using the accumulated movement amount consisting of the angle change amount and the distance measurement information to the obstacle;
The distance traveled by the manned vehicle from the initial position at which it was started, which is calculated using map information of the spatial area used by the unmanned vehicle, the measured number of rotations of the wheels, and the rotation angle of the steering wheel; estimating information about the current position and direction of travel of the robot on the map of the spatial area by using the cumulative amount of movement consisting of the amount of angular change from the initial orientation at the initial position and the distance measurement information to the obstacle;
The unmanned vehicle uses the estimated current position and traveling direction information of the unmanned vehicle and the estimated current position and traveling direction information of the manned vehicle to determine the unmanned vehicle and the manned vehicle. 1. A vehicle travel management system that determines whether or not a vehicle is approaching, and controls the operation of the unmanned vehicle based on the determination result of the approach. The manned vehicle has an obstacle detection sensor that measures the distance to an obstacle in the traveling direction and detects the position of the obstacle, and an encoder that measures the number of rotations of the wheels and the rotation angle of the steering wheel of the manned vehicle. and map information of the space area used by the unmanned vehicle for self-position estimation from the movement of the body of the manned vehicle calculated from the encoder and the obstacle information detected by the obstacle detection sensor. and a self-position estimating unit for estimating information about the current position and traveling direction of the self on the map of the spatial region by using the same calculation as that performed by the unmanned vehicle. The vehicle running management system according to claim 1. The manned vehicle further comprises a self-position information transmitting unit that transmits current position information regarding the current position and traveling direction of the self on the map of the spatial region estimated by the self-position estimating unit,
The present position information is transmitted to the unmanned vehicle by wireless communication, or the current position information is transmitted to the unmanned vehicle traveling in the same spatial area by wireless communication by broadcasting. 2. The vehicle running management system according to 2. The unmanned vehicle is
a vehicle approach determination unit that calculates the distance to another vehicle and determines whether or not another vehicle is approaching the own vehicle;
further comprising a travel stop unit for stopping self travel,
4. The vehicle approach determination unit according to claim 3, wherein when the vehicle approach determination unit determines that the manned vehicle has approached within a predetermined distance, the travel stop unit stops the vehicle from traveling. Vehicle driving management system. The unmanned vehicle is
A first position indicating the current posture of the manned vehicle based on the current position information of the manned vehicle acquired by the position information acquisition unit and the shape information indicating the outer shape of the manned vehicle with point cloud information. A manned vehicle point cloud information generation unit that generates point cloud information of
A self-point cloud that generates a second point cloud information indicating the existence position of an object detected as an obstacle from the distance measurement information of the self-running vehicle and the information on the current position and traveling direction of the self-running car. an information generator;
A point group synthesizing unit for synthesizing the first point cloud information and the second point cloud information to generate obstacle information including the current position of the manned vehicle. Item 4. The vehicle running management system according to item 3. A travel management method for a vehicle travel management system in which a manned vehicle and an unmanned vehicle capable of autonomous travel are connected via a network,
The distance traveled from the initial position at which the unmanned vehicle is started, which is calculated using pre-stored map information of the spatial region in which the unmanned vehicle travels, and the number of rotations of the wheels measured by an encoder, and Information about the current position and traveling direction of the self on the map of the space area from the first accumulated movement amount consisting of the angular change amount from the initial bearing at the initial position and the information about the position of the obstacle existing in the traveling direction. a first self-position estimation step of estimating
The initial position at which the manned vehicle is started, which is calculated by using the map information of the space area used by the unmanned vehicle and the number of rotations of the wheel and the rotation angle of the steering wheel measured by an encoder. Current position of self on the map of the space area from the second cumulative movement amount consisting of the distance moved from the initial position and the amount of angular change from the initial orientation at the initial position, and information on the position of obstacles existing in the traveling direction and a second self-position estimation step of estimating information about the direction of travel;
The unmanned vehicle uses information about the current position and direction of movement of the unmanned vehicle and information about the current position and direction of movement acquired from the manned vehicle, so that the unmanned vehicle approaches the manned vehicle. a first vehicle approach determination step of determining whether or not
When it is determined in the first vehicle proximity determination step that the unmanned vehicle and the manned vehicle are approaching within a predetermined distance, the unmanned vehicle and the manned vehicle are separated from each other. and an unmanned vehicle operation control step for controlling the operation of the unmanned vehicle so that the two vehicles do not collide.

Images