JP2023088367A - Autonomous construction robot control device, autonomous construction robot control system, and control method for autonomous construction robot - Google Patents

Abstract

To provide an autonomous construction robot control device which enables an autonomous robot to grasp an ambient environment.SOLUTION: An autonomous construction robot control device comprises: a sensor data acquisition unit for acquiring waveform data from a sensor which is provided in a target region where a construction is performed and detects vibration; an analysis unit for analyzing a frequency included in the waveform data acquired by the sensor data acquisition unit, and estimating an operation status of a construction machine operated in the target region; and a control unit for outputting to an autonomous construction robot a control signal for operating the robot so as not to interfere with the construction machine based on the operation status of the construction machine.SELECTED DRAWING: Figure 1

Description

The present invention relates to an autonomous construction robot control device, an autonomous construction robot control system, and an autonomous construction robot control method.

Efforts are underway to introduce autonomous robots into construction site management work to improve the efficiency of management work. Self-localization may be used to autonomously drive robots. Self-position estimation is important for patrolling construction sites and acquiring construction data comprehensively.
Indoor positioning technology is used when self-position estimation is performed in a closed space where radio waves from artificial satellites such as GPS (Global Positioning System) do not reach. There are various positioning methods for indoor positioning, and suitable positioning methods differ depending on the purpose, required accuracy, measurement area conditions, and cost. Recently, efforts to increase the accuracy of indoor positioning by combining multiple positioning technologies are becoming mainstream.
In addition, by using SLAM (Simultaneous Localization and Mapping) technology that performs self-location estimation and map creation at the same time, automatic operation of unmanned construction machines in tunnel holes is being realized.

When operating an autonomous robot such as an unmanned construction machine using SLAM technology, it is necessary for the autonomous robot to grasp the situation of the external world. Sensors such as LiDAR (laser scanner), cameras, and ToF (Time Of Flight) sensors are used to grasp the situation of the external world. These sensors acquire point cloud data representing the three-dimensional space of the outside world.

Apart from these techniques, a system for grasping the progress status inside a building under construction has also been proposed (for example, Patent Document 1).

JP 2020-160563 A

However, for example, when an autonomous robot is introduced into the underground space of the reverse construction method, in order to avoid contact with other construction machines operating in the same underground space, it is necessary to grasp the operating status in addition to the position information of the construction machine. There is a need. In the case of an autonomous robot equipped with conventional SLAM technology, it is not possible to sufficiently predict the danger of a construction machine turning while stationary (without changing position information), and it collides (interferes) with the bucket or arm of the construction machine. There is concern that
The system of Patent Literature 1 allows a person to grasp progress information inside a building under construction, but is not intended for an autonomous robot to grasp.

SUMMARY OF THE INVENTION The present invention has been made in view of such circumstances, and its object is to provide an autonomous construction robot control apparatus, an autonomous construction robot control apparatus, and an autonomous construction robot control apparatus that enables an autonomous robot to grasp whether or not there is an object to be detected in its surroundings. An object of the present invention is to provide a robot control system and a control method for an autonomous construction robot.

In order to solve the above-described problems, one aspect of the present invention provides a sensor data acquisition unit that acquires waveform data from a sensor that is provided in a construction target area and detects vibration, and the sensor data acquisition unit acquires waveform data. an analysis unit that analyzes the frequency contained in the waveform data obtained and estimates the operation status of the construction machine operating in the target area; and a controller for outputting a signal to the autonomous construction robot.

Further, one aspect of the present invention includes a sensor that is provided in a target area for construction and detects vibration, a sensor data acquisition unit that acquires waveform data from the sensor, and the waveform data acquired by the sensor data acquisition unit. an analysis unit that analyzes the included frequencies and estimates the operation status of the construction machine operating in the target area; and a controller that outputs to the construction robot.

Another aspect of the present invention is a control method for an autonomous construction robot executed by a computer, wherein the sensor data acquisition unit acquires waveform data from a sensor that detects vibration and is provided in a construction target area. The analysis unit analyzes the frequency included in the waveform data acquired by the sensor data acquisition unit to estimate the operation status of the construction machine operating in the target area, and the control unit estimates the operation status of the construction machine. A control method for an autonomous construction robot for outputting to the autonomous construction robot a control signal for operating the construction machine so as not to interfere with the construction machine.

As described above, according to the present invention, the autonomous robot can determine whether or not there is a detection target in its surroundings, and can operate the autonomous robot without interfering with the detection target. Become.

1 is a schematic diagram showing the configuration of an autonomous construction robot control system S according to one embodiment; FIG. 1 is a schematic functional block diagram showing the configuration of an autonomous construction robot control device 1; FIG. 4 is a diagram showing an example of frequency characteristic data stored in a frequency data storage unit 12; FIG. It is a figure which shows an example of the waveform data detected by the acceleration sensor. 4 is a flowchart for explaining the operation of the autonomous construction robot control device 1;

Hereinafter, an autonomous construction robot control system using an autonomous construction robot control device according to an embodiment of the present invention will be described with reference to the drawings.
FIG. 1 is a schematic diagram showing the configuration of an autonomous construction robot control system S according to one embodiment of the present invention.
The construction site KG is an area where construction using the autonomous construction robot R is performed. For example, the construction site KG is an underground space formed by the reverse construction method. In FIG. 1, the construction site KG is illustrated from above. A retaining wall YK is formed on the inner periphery of the construction site KG.

A plurality of acceleration sensors KS are provided on the retaining wall YK. The acceleration sensor KS is used as a mountain retaining inclinometer for measuring the inclination of the mountain retaining wall YK. This acceleration sensor KS is, for example, a MEMS (Micro Electro Mechanical Systems) sensor. In some cases, such an earth retaining inclinometer is installed in an underground space formed by the upside-down construction method and used to grasp the inclination of the earth retaining. In this embodiment, the acceleration sensor KS is used as a sensor for detecting vibrations occurring in the target area, which is the construction site KG, in addition to grasping the inclination of the earth retaining. Here, by diverting (double-using) the mountain-mounted inclinometer as an acceleration sensor that detects vibrations occurring in the field, there is no need to provide an acceleration sensor separate from the mountain-mounted inclinometer, so installation costs can be reduced. In this case, the acceleration sensor KS detects vibrations occurring within the construction site KG. The vibrations detected here include vibrations caused by the operation of construction machines used at the construction site KG. That is, the acceleration sensor also has a function as a vibration sensor.

The acceleration sensors KS are arranged horizontally (X direction and Y direction) at regular intervals (e.g., several tens of meters pitch) and vertically at regular intervals (e.g., 2 m pitch) so as to surround the excavation area. can be arranged with . By arranging a plurality of acceleration sensors KS in the horizontal direction and the height direction in this way, it is possible to estimate the position of the vibration source generated by the construction machine existing at the construction site KG, and the operating status of the construction machine can be determined in three ways. It can be grasped in dimensional space. That is, it is possible to ascertain at what position in the construction site KG the construction machine is operating. In addition, when a plurality of acceleration sensors KS are provided at different positions in the horizontal direction so as to surround the excavation area (only one in the height direction), the construction in a two-dimensional space in the horizontal direction is required. It is also possible to grasp the position of the machine. In this case, the number of installed acceleration sensors KS can be reduced compared to the case where a plurality of acceleration sensors KS are installed in the height direction.

Moreover, a plurality of construction machines exist at the construction site KG. There are various types of heavy equipment used at the construction site KG, such as a backhoe, a hammer grab dropper, and a breaker. FIG. 1 shows, as an example, a case where there are three construction machines (for example, backhoes). The construction machine J1 and the construction machine J2 are in operation, and there is a possibility that an operation such as turning will be performed. The construction machine J3 is present at the construction site KG, but is in a non-operating state because its operation is turned off.
Here, the construction machine J1 and the construction machine J2 are in an operating state, and even if they do not travel and their current positions do not change, the posture of the construction machines changes when they turn. There is a possibility that the arm will interfere with other objects. Since the construction machine J3 is in a non-operating state and does not turn, its posture is not changed.
Moreover, in this embodiment, the construction machine may be a large-sized heavy machine or a medium-sized heavy machine. Alternatively, a small construction machine may be used as long as the construction machine does not change its position but may change its attitude.

The autonomous construction robot R is an unmanned construction machine that can operate autonomously. The unmanned construction machine may be, for example, a backhoe, a dump truck, a bulldozer, or the like, as long as it can operate unmanned. If the autonomous construction robot R is a backhoe, underground excavation can be realized robotically. When the autonomous construction robot R is a dump truck, it is possible to efficiently transport the goods.
When the movement route (patrol route) IK is specified from the outside, the autonomous construction robot R moves along the movement route. Here, the autonomous construction robot R needs to patrol without interfering with the retaining wall YK and with each construction machine.

FIG. 2 is a schematic functional block diagram showing the configuration of the autonomous construction robot control device 1. As shown in FIG.
The autonomous construction robot control device 1 will be described as being mounted on the autonomous construction robot R, but it is provided outside the autonomous construction robot R and connected to the autonomous construction robot R so as to be communicable. good too. Further, the autonomous construction robot control device 1 may be configured as a server, and may communicate with the autonomous construction robot R by being connected to at least a part thereof via a wireless network.

The autonomous construction robot control device 1 includes a sensor data acquisition section 11 , a frequency data storage section 12 , an analysis section 13 , an object position estimation section 14 , a self-position estimation section 15 and a control section 16 .

The sensor data acquisition unit 11 acquires data from various sensors. Sensors from which the sensor data acquisition unit 11 can acquire various data include an acceleration sensor KS, a thermography camera TH, a positioning sensor LI, and the like.

The sensor data acquisition unit 11 acquires waveform data, which is a detection result of detecting vibration, from an acceleration sensor KS that is provided in a construction target area and detects vibration.

Also, the sensor data acquisition unit 11 acquires temperature distribution data generated in the thermography camera TH. The thermography camera TH is provided in the autonomous construction robot R, analyzes infrared rays emitted from objects existing around the autonomous construction robot R, and generates temperature distribution data representing the temperature distribution from the analysis results. When the autonomous construction robot control device 1 is mounted on the autonomous construction robot R, the thermography camera TH may be provided in the autonomous construction robot control device 1 .

Further, the sensor data acquisition unit 11 acquires positioning data from the positioning sensor LI. Here, the positioning sensor LI may be, for example, any one of LiDER (Light Detection and Ranging), Tof (Time Of Flight) sensor, camera, gyro sensor, and the like. When the positioning sensor LI is LiDAR, the positioning sensor LI generates point cloud data that measures the distance to objects existing in the surrounding three-dimensional space. The positioning sensor LI is mounted on the autonomous construction robot R. Further, when the autonomous construction robot control device 1 is mounted on the autonomous construction robot R, the positioning sensor LI may be mounted on the autonomous construction robot control device 1 .

The frequency data storage unit 12 stores the operation status of the construction machine and the frequency characteristic according to the operation status as frequency characteristic data. FIG. 3 is a diagram showing an example of frequency characteristic data stored in the frequency data storage unit 12. As shown in FIG. The frequency characteristic data includes the type of construction machine, the operating status of the construction machine, frequency, and vibration level.
The type of construction machine represents the type of construction machine. Types of construction machines include, for example, backhoes, hammer grabs, and breakers.
The operating status of the construction machine represents how the construction machine is operating. For example, the operation status of the excavator includes turning, raising the arm, lowering the arm, and the like.
The frequency represents the dominant frequency of vibration that occurs with the operation of the construction machine. For example, the dominant frequencies that occur when a 'backhoe' is 'turning' represent 'f11 to f12'. Such vibrations are caused by the operation of the construction machine and are transmitted through the ground to the retaining wall YK and detected by the acceleration sensor KS. In addition, vibrations caused by the operation of the construction machine may be transmitted to the acceleration sensor KS through the air and detected by the acceleration sensor KS.
Such frequencies differ in main frequencies depending on construction machines and operating conditions. For this frequency, the vibration is measured in advance by the acceleration sensor KS for each situation in which the construction machine is working. The frequency data storage unit 12 stores the measurement results obtained in advance by the acceleration sensor KS in association with the type of construction machine and the operating situation for each situation in which the construction machine is operating.
The vibration level represents the magnitude of vibration caused by the operation of the construction machine. For example, the vibration level generated when the "backhoe" is "turning" is "a11 to a12". Such vibration levels vary depending on construction machines and operating conditions. The vibration level is stored in association with the type of construction machine, the operating situation, and the frequency, which are measured in advance by the acceleration sensor KS, for each operating situation of the machine.

The frequency data storage unit 12 includes a storage medium such as a HDD (Hard Disk Drive), flash memory, EEPROM (Electrically Erasable Programmable Read Only Memory), RAM (Random Access read/write Memory), ROM (Read Only Memory). Memory), or It is configured by any combination of these storage media.
A non-volatile memory, for example, can be used for the frequency data storage unit 12 .

The analysis unit 13 has a frequency analysis unit 131 and a temperature data analysis unit 132 . The analysis unit 13 performs various analyzes on the data obtained from the sensor data acquisition unit 11 .
The frequency analysis unit 131 analyzes the frequencies included in the waveform data acquired by the sensor data acquisition unit 11, and estimates the operation status of the construction machine operating in the target area. For example, the frequency analysis unit 131 extracts frequencies included in the waveform data by performing analysis, refers to the frequency data storage unit 12 for main frequencies among the extracted frequencies, and determines whether the extracted frequencies correspond to the frequencies. The operating status of the construction machine is estimated by reading out the operating status of the construction machine. A characteristic frequency component may be used as the main frequency. As the characteristic frequency component, for example, a frequency component with a certain or more acceleration than other frequency components may be used.
Here, the analysis unit 13 not only analyzes the frequency by the frequency analysis unit 131, but also detects the vibration level based on the amplitude of the waveform data, and detects the vibration level and the main frequency based on the analysis result of the frequency analysis unit 131. By referring to the frequency data storage unit 12 and reading out the type and operation status of the construction machine corresponding to this combination, the operation status of the construction machine may be estimated. This makes it possible to improve the estimation accuracy.

In this way, the frequency analysis unit 131 can grasp the operation status of the construction machine based on the waveform data acquired by the acceleration sensor installed in the construction site. When the vibration source is based on the work of the construction machine, the magnitude and frequency of the vibrating force in the vibration source vary depending on the type of construction machine and the work mode. Therefore, by frequency analysis of the acquired waveform, it is possible to specify the position and type (revolving of the backhoe, dropping of the hammer grab, hitting of the breaker, etc.) in addition to the operation status.

Here, FIG. 4 is a diagram showing an example of waveform data detected by the acceleration sensor KS. In FIG. 4, the horizontal axis represents time (sec) and the vertical axis represents acceleration (G). Here, waveform data (reference numeral 401) measured while various construction machines are not operating at the construction site KG (non-operating), and waveform data measured while a certain construction machine is operating at the construction site KG. Data are superimposed on each other. When the construction machine is not in operation at the construction site KG, the acceleration indicated by the waveform data falls within a certain level. On the other hand, if any construction machine is in operation at the construction site KG, the acceleration generated by the construction machine being in operation is included, so the measured acceleration is higher than the acceleration when the construction machine is not in operation. . Therefore, a reference range (reference numeral 403) is determined in advance based on the acceleration during non-operation, and the analysis unit 13 compares the predetermined reference range with the waveform data, and the acceleration included in the waveform data is used as the reference. If it exceeds the range, it can be determined that the construction machine is operating, and if the acceleration contained in the waveform data does not exceed the reference range, it can be determined that the construction machine is not operating. .
When it is determined that the acceleration included in the waveform data exceeds the reference range, the frequency analysis unit 131 analyzes the frequency component included in the vibration of the waveform data when the acceleration exceeding the reference range is detected. Construction machines in operation can be specified.

The temperature data analysis unit 132 detects whether or not there is a detection target based on the temperature distribution data obtained from the sensor data acquisition unit 11 . For example, the temperature data analysis unit 132 analyzes the temperature distribution data to determine whether the construction machine is in operation and whether there are people (workers, engineers, etc.) working at the construction site KG. To detect.
The temperature data analysis unit 132 detects that a person exists when there is a temperature distribution corresponding to the body temperature of a person in the temperature distribution data. This makes it possible to detect that there are people around the autonomous construction robot R.

If the temperature distribution data has a temperature distribution corresponding to the temperature when the construction machine is in operation, the temperature data analysis unit 132 detects that the construction machine is in operation. As a result, it is possible to detect that there are construction machines in operation around the autonomous construction robot R. FIG.
When construction machinery is in operation, the temperature may be higher than the ambient air temperature by a certain amount (the temperature corresponding to the heat generated by the engine or the heat generated by the motor, etc.), and the temperature is above the threshold. In this case, it can be determined that the construction machine is in operation.

The object position estimation unit 14 estimates the position of the construction machine based on the analysis result of the analysis unit 13 and generates position information based on the estimation result.
For example, the object position estimator 14 estimates the position of the construction machine based on the analysis result of the frequency analyzer 131 . Here, among the waveform data obtained from each of the plurality of acceleration sensors KS, based on the time difference between the times when the operation status of the same construction machine is obtained and the position of each acceleration sensor KS, Estimate the location of construction equipment. For example, the object position estimating unit 14 analyzes the frequencies contained in the waveform data obtained from each acceleration sensor KS, and refers to the frequency data storage unit 12 based on the major frequencies to determine the type of construction machine and its operating status. to estimate Then, when the combination of the same type of construction machine and the operation status is estimated based on each acceleration sensor KS, the object position estimation unit 14 calculates the difference between the arrival times of the main frequencies and each The position of the construction machine can be estimated from the relationship with the position of the acceleration sensor KS. Here, not only the frequency contained in the waveform data but also the vibration level may be used to estimate the type and operating status of the construction machine. In this manner, the object position estimating section 14 can estimate the position of the construction machine based on the positions where the multiple acceleration sensors are provided and the waveform data detected by the multiple acceleration sensors.

Also, the object position estimation unit 14 may estimate the position of the person based on the analysis result of the temperature data analysis unit 132 .
For example, when the temperature data analysis unit 132 detects a temperature distribution corresponding to human body temperature, the object position estimating unit 14 extracts a region corresponding to human body temperature from the temperature distribution data and determines whether the region exists. From the direction and size of the area, the position where the person exists is estimated. Here, the size of the area on the image where the person is detected as being present is determined according to the average height of the person and the distance from the thermography camera TH. Therefore, the object position estimation unit 14 can estimate the distance to the thermography camera TH based on the size of the area where the body temperature of the person is detected, and the area where the body temperature of the person is detected is imaged. By also considering the direction, it is possible to specify the position where a person is estimated to be present.

The object position estimation unit 14 may also estimate the position of the construction machine based on the analysis result of the temperature data analysis unit 132 and the analysis result of the temperature data analysis unit 132 .
The object position estimating unit 14 estimates the position of the construction machine in operation based on the temperature distribution data in which the presence of the construction machine in operation is detected (for example, the position of the pixel) and the photographing direction of the thermography camera TH. Direction can be estimated.
Here, the object position estimation unit 14 extracts an area corresponding to the shape of the construction machine from the distribution of the point cloud data included in the positioning data, and obtains the distance represented by the point cloud data and the point cloud data. Estimate the position where the construction machine is located based on the direction. Then, it is determined whether or not the estimated position of the construction machine matches the direction and distribution (width of distribution) of the construction machine in operation analyzed by the temperature data analysis unit 132, If they match, it can be estimated that the construction machine is in operation at the location where the construction machine is estimated to be.

The self-position estimation unit 15 estimates the position of the autonomous construction robot R to be controlled by the autonomous construction robot controller 1 based on the measurement result of the positioning sensor LI output from the sensor data acquisition unit 11 . The self-location estimation unit 15 can estimate the self-location from the measurement results obtained by the positioning sensor LI by using SLAM (Simultaneous Localization and Mapping) technology. Here, the technique of estimating the self-location by SLAM using LiDAR as the positioning sensor LI may be referred to as LiDAR SLAM. Also, the technique of estimating the self-position by SLAM using a Tof sensor as the positioning sensor LI may be called depth SLAM. Also, the technique of estimating the self-position by SLAM using a camera as the positioning sensor LI may be called Visual SLAM.

The control unit 16 outputs various control signals to the autonomous construction robot R. The control unit 16 has a route generation unit 161 .
When a detection target exists around the autonomous construction robot R, the route generation unit 161 outputs a control signal to the autonomous construction robot R so as not to interfere with the detection target. At least one of an operating construction machine and a person is to be detected.
For example, if there is a construction machine in operation based on the operating status of the construction machine, the route generation unit 161 sends a control signal to the autonomous construction robot R so as not to interfere with the construction machine in operation. Output. When the construction machine in operation is a backhoe, the control unit 16 can control the autonomous construction robot R not to interfere with the backhoe by controlling the autonomous construction robot R not to enter the turning range of the backhoe.
In addition, when the route generation unit 161 detects that there is a person nearby based on the analysis result of the temperature data analysis unit 132, the route generation unit 161 outputs a control signal to the autonomous construction robot R so as not to interfere with the person. . When there are people around, the control unit 16 can control the autonomous construction robot R not to interfere with the people by controlling the autonomous construction robot R not to come within a certain distance from the people.

When performing control so as not to interfere, the route generation unit 161 generates a movement route that does not interfere with the estimated position of the construction machine in operation or the detected person according to the operation status, and the generated movement route Outputs a control signal representing
Further, when performing control so as not to interfere, the control unit 16 does not generate a movement path that does not interfere with the operating construction machine or a person, but instead moves or operates the autonomous construction robot control device 1 (turning, arm movement, etc.). ) may be temporarily stopped to prevent interference. For example, when an operating construction machine or a person passes by the autonomous construction robot R, the autonomous construction robot R temporarily moves from the movement path of the autonomous construction robot R after the construction machine or the person passes by. You may make it continue a movement by canceling a stop. As a result, it is possible to move without interfering with working construction machines (moving construction machines) or people. Here, not only is the autonomous construction robot R temporarily stopped so as not to interfere, but also the movement speed of the autonomous construction robot R is decelerated. may be paused.

The above-described sensor data acquisition unit 11, analysis unit 13, object position estimation unit 14, self-position estimation unit 15, and control unit 16 may be configured by a processing device such as a CPU (central processing unit) or a dedicated electronic circuit. .

FIG. 5 is a flowchart for explaining the operation of the autonomous construction robot control device 1. As shown in FIG.
The autonomous construction robot control device 1 is mounted on, for example, the autonomous construction robot R, and executes processing when the autonomous construction robot R is powered on.
The sensor data acquisition unit 11 of the autonomous construction robot control device 1 acquires measurement results from each sensor (step S101).
When the sensor data acquisition unit 11 acquires the measurement results, the analysis unit 13 performs analysis based on the measurement results acquired by the sensor data acquisition unit 11 . Here, the analysis unit 13 analyzes whether or not there is a person around the autonomous construction robot R, and whether or not there is a construction machine in operation within the construction site KG (step S102).
When the analysis unit 13 detects that there is no person around the autonomous construction robot R and that there is no construction machine in operation within the construction site KG, the analysis unit 13 advances the process to step 101 (step S103-NO).

On the other hand, the analysis unit 13 determines whether at least one of the case where it is detected that there are people around the autonomous construction robot R and the case where it is detected that there is a construction machine in operation at the construction site KG is detected. If detected (step S103-YES), the object position estimation unit 14 is notified that the detection target has been detected. The object position estimation unit 14 estimates the detected position of the detection target (step S104). For example, when a person is detected in the analysis result of the analysis unit 13, the object position estimation unit 14 estimates the position where the person is present, and the analysis result of the analysis unit 13 indicates that there is a construction machine in operation. is detected, the position of the construction machine in operation is estimated.

On the other hand, the self-position estimation unit 15 acquires data measured by LiDAR from the sensor data acquisition unit 11 at regular intervals, and estimates the self-position of the autonomous construction robot R.

When the position of the detection target is estimated by the object position estimation unit 14, the route generation unit 161 of the control unit 16 generates a movement route that does not interfere with the detection target (step S105). Output to the mold construction robot R (step S106). The autonomous construction robot R moves based on the movement route output from the control unit 16 .
On the other hand, the control unit 16 determines whether or not to end the operation of the autonomous construction robot R (step S107). If the process is terminated (step S107-YES) and the operation of the autonomous construction robot R is not terminated, the process proceeds to step S101.

According to the embodiment described above, by analyzing the waveform data acquired by the multiple acceleration sensors (MEMS sensors) provided on the earth retaining wall, it is possible to determine the operation status, position and type of construction machinery in the underground space of the reverse construction method. can be determined immediately and accurately.
Further, according to the embodiment described above, in addition to the self-position estimation using the conventional SLAM technology, the operation status of the construction machine can be grasped based on the waveform data acquired by the acceleration sensor installed in the construction site. can do. Then, when it is detected that there is a construction machine in operation, the moving route is generated again. The autonomous construction robot R can safely patrol the site while appropriately resetting so as to move along a movement route that does not approach the area where the operation of the construction machine has been determined.
In addition, in the above-described embodiment, it is possible to safely and inexpensively operate an autonomous robot equipped with SLAM technology in a narrow space where construction machinery can operate, such as an underground space using an upside-down construction method. Since the autonomous robot can be easily introduced to such underground construction work, the autonomous construction robot control device 1 described above contributes to the efficiency of management work and the improvement of productivity.

In addition, according to the above-described embodiment, it is possible to grasp the status of whether or not the construction machine is operating, the position at which it is operating, etc. Therefore, by grasping the operating status, it is possible to perform construction work in the underground space. You can also check your progress.

Further, for example, in the above-described embodiment, when it is detected that the construction machine is operating in the target area, the autonomous construction robot control device 1 causes the autonomous construction robot to temporarily stop or move to the target area. It is possible to generate a movement route that bypasses the , and send it to the autonomous construction robot. As a result, when the construction machine is operating in the target area, the autonomous construction robot is temporarily stopped, and when it is detected that the construction machine is in an operating state in which the posture does not change (for example, the If not changed), the movement may be resumed.

In addition, when it is detected that the construction machine is in an operating state in which the posture is not changed in the target area (a situation in which the machine is not operating, or an operation involving a change in the (e.g., when construction machinery is not available), move along the movement route generated in advance, and if the construction machinery is operating in the target area, create a movement route that bypasses the area where the construction machinery is operating. It may be regenerated. As a result, the autonomous construction robot moves along a predetermined movement route when the construction machine's posture does not change in the target area, and when the construction machine is operating in the target area. can be moved around so as not to interfere with the construction machine.

In the above-described embodiment, the frequency analysis unit 131 refers to the frequency data storage unit 12 to estimate the operating status. The operating status may be estimated.
For example, data indicating the operation status of a construction machine is attached to waveform data as a teacher label, and a learning device learns the relationship between the waveform data and the operation status of the construction machine to generate a trained model. may Machine learning, deep learning, or the like may be used as a method of learning in the learning device. Then, the frequency analysis unit 131 may obtain the operation status of the construction machine by inputting the waveform data obtained from the sensor data acquisition unit 11 to the trained model obtained from the learning device.

In the above-described embodiment, the case where the construction site KG is an underground space formed by the reverse construction method has been described. If it is possible to do so, it may be other than the underground space formed by the reverse construction method. For example, the construction site KG may be a tunnel pit.

The autonomous construction robot control device 1 in the above-described embodiment may be realized by a computer. In that case, a program for realizing this function may be recorded in a computer-readable recording medium, and the program recorded in this recording medium may be read into a computer system and executed. It should be noted that the "computer system" referred to here includes hardware such as an OS and peripheral devices. The term "computer-readable recording medium" refers to portable media such as flexible discs, magneto-optical discs, ROMs and CD-ROMs, and storage devices such as hard discs incorporated in computer systems. Furthermore, "computer-readable recording medium" refers to a program that dynamically retains programs for a short period of time, like a communication line when transmitting a program via a network such as the Internet or a communication line such as a telephone line. It may also include something that holds the program for a certain period of time, such as a volatile memory inside a computer system that serves as a server or client in that case. Further, the program may be for realizing a part of the functions described above, or may be capable of realizing the functions described above in combination with a program already recorded in the computer system. It may be implemented using a programmable logic device such as an FPGA (Field Programmable Gate Array).

Although the embodiment of the present invention has been described in detail with reference to the drawings, the specific configuration is not limited to this embodiment, and design and the like are included within the scope of the gist of the present invention.

DESCRIPTION OF SYMBOLS 1... Autonomous construction robot control apparatus 11... Sensor data acquisition part 12... Frequency data storage part 13... Analysis part 14... Object position estimation part 15... Self-position estimation part 16... Control part 101... Step , 131 ... frequency analysis unit, 132 ... temperature data analysis unit, 161 ... route generation unit

Claims (7)

A sensor data acquisition unit that acquires waveform data from a sensor that detects vibration and is provided in a target area for construction;
an analysis unit that analyzes the frequencies contained in the waveform data acquired by the sensor data acquisition unit and estimates the operation status of the construction machine operating in the target area;
a control unit that outputs a control signal to the autonomous construction robot to operate the construction machine so as not to interfere with the construction machine, based on the operation status of the construction machine;
An autonomous construction robot controller having a frequency data storage unit that stores an operation status of the construction machine and a frequency characteristic according to the operation status;
The autonomous construction robot control device according to claim 1, wherein the analysis unit estimates the operation status by referring to the frequency data storage unit and acquiring the operation status corresponding to the frequency obtained by the analysis. at least one of said sensors is a thermographic camera;
The sensor data acquisition unit acquires temperature distribution data obtained from the thermography camera,
The analysis unit detects whether or not a detection target exists based on the temperature distribution data,
3. The autonomous construction robot control device according to claim 1, wherein, when the detection target exists, the control unit outputs a control signal to the autonomous construction robot so as not to interfere with the detection target. an object position estimation unit that generates position information by estimating the position of the construction machine based on the analysis result of the analysis unit;
4. The control unit according to any one of claims 1 to 3, wherein the control unit generates a movement route that does not interfere with the estimated position according to the operating status, and outputs a control signal representing the generated movement route. An autonomous construction robot controller as described. The sensors are a plurality of acceleration sensors that detect acceleration based on the vibration and are provided at different positions so as to surround the target area,
5. The object position estimator according to claim 4, wherein the object position estimator estimates the position of the construction machine based on the positions where the plurality of acceleration sensors are provided and waveform data respectively detected by the plurality of acceleration sensors. Autonomous construction robot controller. a sensor for detecting vibrations provided in the target area for construction;
a sensor data acquisition unit that acquires waveform data from the sensor;
an analysis unit that analyzes the frequencies contained in the waveform data acquired by the sensor data acquisition unit and estimates the operation status of the construction machine operating in the target area;
a control unit that outputs a control signal to the autonomous construction robot based on the operating status of the construction machine so as not to interfere with the construction machine;
An autonomous construction robot control system with A computer-implemented method for controlling an autonomous construction robot, comprising:
A sensor data acquisition unit acquires waveform data from a sensor that detects vibration and is provided in the target area for construction,
an analysis unit that analyzes the frequency included in the waveform data acquired by the sensor data acquisition unit and estimates the operation status of the construction machine operating in the target area;
A control method for an autonomous construction robot, wherein a control unit outputs a control signal to the autonomous construction robot so as not to interfere with the construction machine, based on the operation status of the construction machine.

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