CN108873899B - Obstacle avoidance method of dust collection robot - Google Patents
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Abstract
The invention discloses an obstacle avoidance method of a dust collection robot, which comprises the steps of walking along a track, comparing a measurement result, executing a first turning mode or executing a second turning mode and the like. The obstacle avoidance method can avoid oblique obstacles and can detour according to the size of the oblique angle of the obstacles. The invention also discloses a method for establishing the grid map.
Description
Technical Field
The invention relates to an obstacle avoidance method of a dust collection robot, and belongs to the field of intelligent home furnishing.
Background
The existing obstacle avoidance method of the dust collection robot mainly comprises accurate obstacle avoidance and fuzzy obstacle avoidance. The mobile robot path planning (university of electric power university, university of northeast, university of great university, mengxu) discloses a fuzzy obstacle avoidance method, which adopts a fuzzy logic algorithm, is relatively large in computation, and is not suitable for a low-cost dust collection robot. And the design of a hybrid perception system and obstacle avoidance planning of an autonomous dust collection robot based on the kiren neural network (university of Zhejiang university, Master academic paper, brave) discloses an intelligent obstacle avoidance algorithm of a dust collection robot based on the neural network, which is not perfect enough and is difficult to be applied to an actual dust collection robot. The robot traversal algorithm based on unknown environment (university of Kunming Master's academic thesis, Wangyu) discloses a multiple obstacle avoidance method for a dust collection robot, but as described in the scheme, the obstacle avoidance method is mostly applicable to right-angle obstacles.
Disclosure of Invention
The invention provides an obstacle avoidance method of a dust collection robot, which can avoid oblique-angle obstacles and can detour according to the size of oblique angles of the obstacles.
The technical scheme of the invention is realized as follows:
an obstacle avoidance method of a dust collection robot is characterized by comprising the following steps:
step 331: walking along the track, measuring s2, s3, s4 and s5 values, entering step332 or step333 according to the measurement result,
step 332: if s2, s3, s4, s5 are all greater than d, step334, step335 or step336 is entered depending on the value of s2,
step 333: if any item of s2, s3, s4 or s5 is less than or equal to d, finding an inaccessible boundary, rotating in place to s1 ═ d, entering step334, step335 or step336 according to the value of s2,
step 334: if s2 is less than
Finding the physical boundary, and executing the first turning mode until
Returning to the step331, the process returns to step331,
first bending mode
Angular velocity ω of C1 side wheel1Angular velocity ω of C2 side wheel2，
step 335: if s2 is greater than
Finding the working area, and executing a second turning mode until
Returning to the step331, the process returns to step331,
second turning mode
Angular velocity ω of outer wheel1Inner wheel angular velocity omega2，
ω1＝ωp,＝，
step 336: if it is
Returning to step 331.
A method for establishing a grid map is characterized by comprising the steps of presetting a system, establishing a maximum working area, performing internal circulation traversal and establishing a working grid network, wherein an obstacle avoidance method of a dust collection robot is executed in the process of establishing the maximum working area and performing the internal circulation traversal.
In the method of establishing a grid map of the present invention, the system presets including:
step 11: at least two absolute reference points O1, O2,
step 12: walking sensors C1, C2, C3, C4 and C5 are arranged on the outer side of the vehicle body, the included angles of adjacent walking sensors are all 45 degrees, C3 is arranged right in front of the advancing direction of the dust collector, C1 and C5 are respectively positioned on the axis of the wheel, the sum of the distance between each sensor and the entity and the radius of the vehicle body is defined as s1, s2, s3, s4 and s5,
step 13: defining the diameter B of the dust collector, the distance D of wheels of the dust collector and the rotating speed omega of the wheels on the side C11C2 side wheel speed ω2，
step 14: c1 is a vehicle body reference point O3, C5 is a vehicle body reference point O4, a system preset safety distance d,
step 15: the dust collector walks to any one of s1, s2, s3, s4 and s5 in a straight line along the current direction until d is equal to d, a leveling mode is executed, a coordinate system (xoy) is established by taking the position of O3 as an origin at the moment, x is the traveling direction of the vehicle body, step 16: the distances (a, b) of the origin from the O1, O2 reference points are detected and stored.
In the method of creating a grid map of the present invention, the creating a maximum work area includes:
step 21: to be provided with
And s1 is d walking, avoiding obstacles, recording O3 track (x, y) and O4 track (x ', y'),
step 22: if (x, y) is (0, 0), the maximum working area y is F (x) generated according to the O3 track line, and the virtual boundary line y' is g generated according to the O4 track linei(x′)，t＝0。
In the method of establishing a grid map of a dust collection robot of the present invention, the inner loop traversal includes:
step 31: t +1, according to y ═ gt-1(x') establishing the t-th O3 preset route (x)t，yt)，xt，ytIs a coordinate value, yt＝gt-1(xt)，
step 32: calibration O3 starting Point (x)min,ymin) Walking along a preset route, recording an O3 track line (x, y) and an O4 track (x ', y'),
step 33: when the walking is carried out, the obstacle is avoided,
step 34: if the current track (x, y) is (x)t，yt) And then the vehicle runs along the preset route again,
step 35: if (x, y) ═ xmin,ymin) Generating the t-th track line y ═ f from the O3 trackt(x) The t-th virtual boundary line y' is generated from the O4 locus as gt(x′)，
step 36: if this trace coincides with any previously stored trace, step40 is entered, otherwise step31 is returned.
In the method of creating a grid map of the present invention, the inner loop traversal comprises:
step 31: t +1, according to y ═ gt-1(x') establishing the t-th O3 preset route (x)t，yt，θt)，xt，ytIs a coordinate value of θtIs a corner, yt＝gt-1(xt)，θt＝gt-1′(xt)，gt-1Is' gt-1At xtThe derivative of (a) of (b),
step 32: calibration O3 starting Point (x)min,ymin) Walking along a preset route, avoiding obstacles, recording an O3 track line (x, y) and an O4 track (x ', y'),
step 33: if the current track (x, y) is (x)t，yt) And then the vehicle runs along the preset route again,
step 34: if (x, y) ═ xmin,ymin) Generating the t-th track line y ═ f from the O3 trackt(x) The t-th virtual boundary line y' is generated from the O4 locus as gt(x′)，
step 35: if this trace coincides with any previously stored trace, then traversal is complete, otherwise return to step 31.
The obstacle avoidance method can avoid oblique obstacles and can detour according to the size of the oblique angle of the obstacles.
Drawings
FIG. 1 is a schematic view of a right turn around an obstacle of the robot for dust collection of the present invention;
FIG. 2 is a schematic view of the right turn of the robot for cleaning of the present invention around another obstacle;
FIG. 3 is a schematic view of the right turn of the robot for cleaning according to the present invention, bypassing another obstacle;
FIG. 4 is a schematic view of the cleaning robot of the present invention turning left around an obstacle;
FIG. 5 is a schematic view of the cleaning robot of the present invention turning left around another obstacle;
FIG. 6 is a schematic view of the cleaning robot of the present invention turning left around another obstacle;
FIG. 7 is a flow chart of a method of building a grid map of a dust collection robot according to the present invention;
FIG. 8 is a preset schematic view of a dust collection robot system according to the present invention;
fig. 9 is a schematic view of a working area of the dust collecting robot of the present invention;
FIG. 10 is a schematic diagram of a path of the robot for cleaning the work area;
FIG. 11 is a schematic view of a rasterized work area of the present invention;
FIG. 12 is a two-time trace diagram of the dust extraction robot of the present invention, showing primarily the establishment of the next trace based on the previous trace;
FIG. 13 is a schematic view of the robot cleaner of the present invention circumventing obstacles;
fig. 14 is a schematic view of the cleaning robot of the present invention approaching a wall to find an initial point.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
Overview of the prior art
The existing obstacle avoidance method of the dust collection robot mainly comprises accurate obstacle avoidance and fuzzy obstacle avoidance. The mobile robot path planning (university of electric power university, university of northeast, university of great university, mengxu) discloses a fuzzy obstacle avoidance method, which adopts a fuzzy logic algorithm, is relatively large in computation, and is not suitable for a low-cost dust collection robot. And the design of a hybrid perception system and obstacle avoidance planning of an autonomous dust collection robot based on the kiren neural network (university of Zhejiang university, Master academic paper, brave) discloses an intelligent obstacle avoidance algorithm of a dust collection robot based on the neural network, which is not perfect enough and is difficult to be applied to an actual dust collection robot. The robot traversal algorithm based on unknown environment (university of Kunming Master's academic thesis, Wangyu) discloses a multiple obstacle avoidance method for a dust collection robot, but as described in the scheme, the obstacle avoidance method is mostly suitable for right-angle obstacles, and a large number of inaccessible spaces (missing grids) are generated by bypassing oblique-angle obstacles or wall obstacles.
In the prior art, map components of the dust collection robot mostly adopt a grid method, and the grid method can reduce the data volume of a system and is easy to maintain and plan a path. The premise of the grid method is that the working interval is read, and the prior art mostly adopts the edgewise walking, and the method is also applied. The premise of internal circulation traversal is that the edge walking obtains the maximum working environment. Research on an intelligent dust collection robot navigation system based on an ultrasonic sensor (university of Zhejiang university Master's academic thesis, King fire) discloses a map reading mode. Design and implementation of a path covering system of a home cleaning robot (university of Harbin university of Master academic thesis, Zhou Yao) performs grid assignment while performing loop traversal, and does not pay attention to correction of a traversal route. Meanwhile, there is inevitably a path overlap during the loop traversal, and this document does not pay attention to eliminate a part of the repetitive calculation. Positioning navigation of a dust collection robot based on three-dimensional reconstruction (Master academic paper of Jilin university, Zhangming) discloses a rasterization method based on camera data reading. The method determines the content of the grid based on whether the route passes through a predetermined grid or not. Such a route is defined as a trajectory route of the center of the vehicle body. In an actual map, even if a grid through which a trajectory route of a road in a vehicle body passes is not necessarily accessible to all grids themselves. Defining an inaccessible grid as a working grid can cause confusion in the robot work. This document also discloses positioning techniques for a vacuum robot, which may be referred to in this application.
There are various internal circulation traversals of the working interval, and the prior art mainly focuses on three methods of region segmentation, dressing traversal and spiral traversal. Dressing traversal is the most common in the prior art, and the system is simple in operation, but if an obstacle exists in the middle of a working area, the system generates many repeated paths for covering the working area behind the obstacle. The region segmentation can solve the path planning when the working region has obstacles, and the method refers to the cleaning robot full coverage path planning research (Chongqing university Master academic paper, Zhang Yue). For walls and obstacles with long slopes, the efficiency of area segmentation is low. The research on cleaning robots based on ARM controllers (master academic thesis of university of western science and technology, king loyalty front) adopts a broken line approaching walking mode in selecting path planning, which can bypass an oblique obstacle and is also referred to in the present application. The spiral traversal can deal with the inclined wall, but the prior art does not solve the problem of how to select the reference after the inclined wall is separated from the wall during internal circulation.
As shown in fig. 1 to 6, the obstacle avoidance method of the present invention can be used for avoiding fixed obstacles with regular shapes, and is particularly suitable for avoiding walls or cabinets with oblique angles. The obstacle avoidance method comprises the following steps: step 01: and (4) walking along the track, measuring s2, s3, s4 and s5 values, and entering step02 or step03 according to the measurement result. The measurement results show that the robot for dust collection faces obstacles in different states. If s2, s3, s4, s5 are all greater than d and
refer to fig. 11. The robot cleaner enters an enlarged work area and the cleaner executes and flips outwardly along the front barrier. If s2, s3, s4, s5 are all greater than d and
referring to fig. 8 to 9, a diagonal entity is found on the right side. The cleaner turns and follows a new path straight. If any of s2, s3, s4, s5 is less than or equal to d, referring to fig. 10, an oblique entity is found at the front or left side, the front is not accessible, the original site rotates at a large angle and returns along a new route.
The invention realizes turning at different angles by using the difference of the rotating speeds of wheels, and the motion state of the dust collection robot is described in the research on the whole-area path planning and obstacle avoidance of the indoor cleaning robot (university in south of the Yangtze river, Zen Cen). Specifically, step 02: if s2, s3, s4, s5 are all greater than d, step04, step05 or step06 is entered depending on the value of s 2. step 03: if any one of s2, s3, s4 and s5 is less than or equal to d, the boundary is found to be inaccessible, and after the boundary is rotated in place to s1 ═ d, the boundary enters step04, step05 or step06 according to the value of s 2. step 04: if s2 is less than
Finding the physical boundary, and executing the first turning mode until
Returning to step 01. step 05: if s2 is greater than
Finding the working area, and executing a second turning mode until
Returning to step 01. step 06: if it is
Returning to step 01. In the present invention, the rotation modes of the dust collection robot are divided into three types: right turns of the work area occur on the right side, left turns of a solid obstacle occur on the right side, and pivot rotation of the obstacle occurs right ahead or on the left side. In-situ rotation is a rotation about the centre of rotation, omega, of the vacuum robot1＝ωp，ω2＝-ωp. To increase the walking area of the dust collection robot to the maximum extentThe area which can not be traversed can be reduced, the dust collection robot needs to walk close to the side, and one of feasible methods is to limit the turning radius of right turning and left turning. The right turning adopts a first turning mode:
and the left turn adopts a second turning mode:
ω1＝ωp，
referring to fig. 7 to 14, the invention discloses a method for establishing a grid map of a dust collection robot, which comprises the steps of system presetting, establishment of a maximum working area, internal circulation traversal and establishment of a working grid network. The method can be embedded into the existing hardware system of the dust collection robot on the basis of installing a preset number of sensors. The hardware system can comprise a microprocessor unit, a sensor unit and a driving execution unit. The sensor unit mainly comprises five ultrasonic sensors, a collision sensor and a Hall sensor which are arranged on the periphery of the front side of the dust collection robot. The drive execution unit comprises a stepping motor control module and left and right stepping motors. The microprocessor unit comprises a main control module, a display module, a communication module and the like. The specific structure can be described in "research on cleaning robot based on ARM controller" (master academic thesis of university of science and technology in western river, royal loyalty) and the like.
The system presetting refers to setting the space size of the robot and arranging a sensor at a specified position of the dust collection robot. It broadly comprises the following steps. step 11: at least two absolute reference points O1, O2 are set on one side of the sweeping area. The absolute reference points are arranged on one side of the wall, and the two absolute reference points can determine the current absolute position of the dust collection robot.After the working map is established, the dust collection robot started at any place can determine the position information of the working map where the dust collection robot is located. step 12: walking sensors C1, C2, C3, C4 and C5 are arranged on the outer side of the vehicle body, the included angles of adjacent walking sensors are all 45 degrees, C3 is arranged right in front of the advancing direction of the dust collector, C1 and C5 are respectively positioned on the axis of the wheel, and the sum of the distance between each sensor and the entity and the radius of the vehicle body is defined as s1, s2, s3, s4 and s 5. The dust collection robot determines the distance between the vehicle body and the wall and other obstacles according to the positions of the sensors. The sum of this distance and the vehicle body radius represents the distance (s1, s2, s3, s4, s5) of the geometric circle of the vehicle body from the obstacle. The sensor is, for example, an ultrasonic distance measuring sensor adopted in research on autonomous dust collection robot driven by an ultrasonic motor (Nanjing aerospace university, Wang Macro), research on autonomous mobile robot navigation system based on ultrasonic distance measuring technology (Wuhan university of Argania), and the like. step 13: defining the diameter B of the dust collector, the distance D of wheels of the dust collector and the rotating speed omega of the wheels on the side C11C2 side wheel speed ω2. Rated speed omega of wheelp. Generally, a driving motor of the dust collection robot adopts angular velocity coding, and the definition of the angular velocity is more beneficial to measuring the state of a vehicle body.
step 14: c1 is a vehicle body reference point O3, C5 is a vehicle body reference point O4, and the system presets a safety distance d. O3 and O4 are used to record the positions of the inside and outside of the vehicle body. d is greater than
About 50 mm. This distance prevents any position of the vehicle body from colliding with an obstacle. step15 and step16 are used to find the initial point next to the wall. step 15: and the dust collection robot linearly walks along the current direction until any item of s1, s2, s3, s4 or s5 is equal to d. After obstacle avoidance is finished, a coordinate system (xoy) is established by taking the position of O3 at the moment as an origin, and x is the advancing direction of the vehicle body. step 16: the distances (a, b) of the origin from the O1, O2 reference points are detected and stored. The invention does not limit the coordinate positioning method of the dust collection robot, and a wheel pulse positioning method can be adopted, as described in research on autonomous path planning method under the unstructured environment of the dust collection robot (university of Zhejiang university, university of Master academic thesis, Von Shenkun). Dust collection robotControlling the distance from the edge, walking along the edge, and finely adjusting the walking direction according to the change of the wall body. In order to avoid measurement errors (accidental errors) caused by abnormal transformation of obstacles, the method can adopt software jitter elimination filtering, mainly utilizes time delay detection in the programming process of a program, detects the ultrasonic signals again after 30 to 50ms of delay after the ultrasonic signals meeting the requirements are detected, and if data in an error range are still detected, the data signals are considered to be correct and credible. Meanwhile, the system can reduce the error (system error) in the measurement mode by adopting Kalman filtering. The kalman filtering method is well known to those skilled in the art and will not be described herein, and the specific structural principle thereof can be described in "research on design and path planning of intelligent cleaning robot" (university of harbourne industries, zhang).
The maximum working area is established by walking for one circle along the indoor and outdoor side walls, recording the maximum coordinate position of the room and providing external reference for the subsequent traversal of the working area. This step can also be called walking along the edge, and the prior art has disclosed feasible implementation algorithms, such as "research on design and path planning of intelligent cleaning robot" (hai shun industrial university, zhang chao) "," research on autonomous path planning method in unstructured environment of dust collection robot "(chessman paper of university in zhejiang, von kun)", and so on. step 21: to be provided with
And s1 ═ d walking, obstacle avoidance, recording O3 track (x, y) and O4 track (x ', y'). step 22: if (x, y) is (0, 0), the maximum working area y is f (x) generated according to the O3 trajectory, and the virtual boundary line y' is g generated according to the O4 trajectoryi(x'), t ═ 0. The virtual boundary line is the expected trajectory of the next O3.
The internal circulation traversal refers to that the whole working area is spirally traversed in the maximum working area, and the space which cannot be accessed is recorded as an obstacle, so that all areas which can be walked are determined. In the prior art, the internal circulation traversal mostly adopts a back-turning reciprocating walking mode, and the mode is easy to generate blind areas. The method adopts a spiral traversal mode, and reduces the existence of blind areas. step 31: t +1, rootAccording to y ═ gt-1(x') establishing the t-th O3 preset route (x)t，yt，θt)，xt，ytIs a coordinate value of θtIs a corner, yt＝gt-1(xt)，θt＝gt-1′(xt)，gt-1Is' gt-1At xtThe derivative of (c). The coordinates defining the state of the robot cleaner may include direction coordinates in addition to coordinates of the index point. In order to smooth the movement of the vehicle body, the walking direction is determined by the derivative of the preset route. step 32: calibration O3 starting Point (x)min,ymin) The starting point is generally the position on the preset route closest to the last trajectory end point. The dust collection robot walks along a preset route, avoids obstacles, and records an O3 track line (x, y) and an O4 track (x ', y'). During actual walking, the O3 track line (x, y) and the preset route (x) are in the presence of obstaclest，yt，θt) Are not completely identical. step 33: if the current track (x, y) is (x)t，yt) And indicating that the dust collection robot bypasses the obstacle and runs along the preset route again. step 34: if (x, y) ═ xmin,ymin) It means that the robot cleaner has returned to the initial point of the present travel route. The system generates the t-th track line y-f according to the O3 trackt(x) The t-th virtual boundary line y' is generated from the O4 locus as gt(x'). step 35: if the trace line of the time is overlapped with any previously stored trace line, the dust collection robot is indicated to enter the circulation route, and traversal is completed. Otherwise, return to step31 and go through the inner loop again. When a tiny irregular obstacle exists in the operation center of the dust collection robot, the efficiency of the internal circulation traversal is low. However, considering that the indoor environment is mostly a regular space, and the possibility that the obstacle is just at the inner circulation center of the dust collection robot is low, the inner circulation traversal method has feasibility.
The working grid network is established by a method of dividing a working area into grid networks after the dust collection robot traverses the working area. step 41: defining a rectangular area (H)width，Hl.n) And divides the rectangular area into a plurality of grids (i,j)，Hwidthis the maximum x value of y ═ F (x), Hl.nThe maximum value of y is, i is x/B, and j is y/B. The coordinates of the grid (i, j) are defined relative to absolute reference points O1 and O2, and the position of the grid map can be determined by measuring the positions of the cleaning robot relative to the reference points O1 and O2 whenever the cleaning robot is started to operate, so that the cleaning robot is prevented from recording the position of the cleaning robot at any time. step 42: definition of CellValue [ i ]][j]Y ═ f (x) or y ═ ft(x) When only one or zero set of tracks passes through the grid (i, j), CellValue [ i][j]0, otherwise CellValue [ i ═ 0][j]A grid map is stored, 1. Meanwhile, when the two groups of tracks pass through the grids (i, j), the fact that the dust collection robot traverses the work map enters the grids is shown, and the grids are in an accessible state integrally. Only one set of traces enters the grid or no traces enter the grid, indicating that the grid as a whole is in a non-accessible state. Although this storage determination manner may determine a part of a small area (smaller than the size of the dust collection robot) as inaccessible to the grid, it is desirable to give up a part of the space and improve the storage efficiency and the path planning efficiency with respect to the entire space to be cleaned.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (1)
1. An obstacle avoidance method of a dust collection robot is characterized by comprising the following steps:
step 331: walking along the track, measuring
The value, depending on the measurement result, enters step332 or step333,
step 332: if it is
Are all greater than
According to the value of s2, step334, step335 or step336 is entered,
step 333: if it is
Any one of less than or equal to
Finding an inaccessible boundary, rotate in place to s1
Then step334, step335 or step336 according to the value of s2,
step 334: if s2 is less than
d, finding the solid boundary, and executing the first turning mode until
d, returning to step331,
a first bending mode:
c1 side wheel angular velocity
Angular velocity of C2 side wheel
，
step 335: if s2 is greater than
d, finding the working area and executing a second turning mode until
d, returning to step331,
the second turning mode:
angular velocity of outside wheel
Inner wheel angular velocity
，
step 336: if it is
d, returning to step331,
and, the system presets a safe distance d, sets the space size of the dust collection robot and arranges a sensor at a designated position of the dust collection robot, including the following steps,
step 11: at least two absolute reference points O1, O2 are set at one side of the sweeping area, the absolute reference points are set at one side of the wall,
step 12: walking sensors C1, C2, C3, C4 and C5 are arranged on the outer side of the dust collection robot, the included angles of adjacent walking sensors are both 45 degrees, C3 is arranged right in front of the advancing direction of the dust collection robot, C1 and C5 are respectively positioned on the wheel axis, the sum of the distance between each sensor and an entity and the radius of the dust collection robot is defined as s1, s2, s3, s4 and s5, the distance between the dust collection robot and a wall and other obstacles is determined by the dust collection robot according to the position of each sensor,
step 13: dust collection definitionDiameter of robot B, wheel distance of dust collector D, and rated rotation speed of wheel
。
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| Publication number | Priority date | Publication date | Assignee | Title |
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