Self-adaptive obstacle avoidance control method and device of warehouse robot and storage medium

Abstract

The invention relates to the technical field of intelligent warehousing, and discloses a self-adaptive obstacle avoidance method and device for a warehouse robot and a storage medium, and the method comprises the following steps: obtaining the path width of an area in front of the robot; the expansion width of the obstacle is set according to the path width of the front area, and the expansion width and the path width are in positive correlation within a certain range; detecting the size of an obstacle in the scene, and expanding the boundary of the obstacle detected in the scene according to the set expansion width; and guiding the robot to avoid the obstacle according to the boundary of the expanded obstacle. According to the obstacle avoidance method, the expansion width is adaptively set according to the width of the front path, the situation that the posture adjustment range of the robot is too narrow during obstacle avoidance due to the too large expansion width when the robot passes through the narrow area is avoided, and therefore the situation that the robot needs to spend a large amount of time to adjust the posture when passing through the narrow area due to the too large expansion width is avoided; the method can improve the adaptability to a narrow area.

Description

Technical Field

[0001] The present invention relates to the field of intelligent warehousing technology, and in particular to an adaptive obstacle avoidance control method, device and storage medium for a warehouse robot. Background Art

[0002] With the development of automatic navigation technology, more and more logistics warehouses and factories have begun to use AGV robots to complete the handling of goods, products and production materials. In order to prevent the robot from colliding with obstacles during operation, in SLAM navigation technology, a distance is usually set for the detected obstacle to prevent the robot from getting too close to the obstacle. In the existing robot navigation scheme, the value of Di st is fixed, which will cause the robot to spend a lot of time to adjust the robot's posture when passing through a narrow area. The robot's adaptability is poor and it is difficult to adapt to factory warehouses with limited space and dense shelves, such as lithium battery warehouses. Summary of the invention

[0003] In order to overcome the deficiencies of the prior art, the purpose of the present invention is to provide an adaptive obstacle avoidance system for a warehouse robot, which can adjust the expansion width of obstacles in real time according to the path width, reduce the difficulty of the robot passing through narrow areas, and improve the robot's adaptability to narrow spaces.

[0004] To solve the above problems, the technical solution adopted by the present invention is as follows: an adaptive obstacle avoidance method for a warehouse robot, comprising the following steps:

[0005] Get the path width of the area in front of the robot;

[0006] The expansion width of the obstacle is set according to the path width of the front area, so that the expansion width and the path width are positively correlated within a certain range;

[0007] Detect the size of obstacles in the scene and expand the boundaries of the obstacles detected in the scene according to the set expansion width;

[0008] The robot is guided to avoid the obstacle according to the expanded boundary of the obstacle.

[0009] Compared with the prior art, the beneficial effect of the present invention is that the expansion width of the obstacle is adjusted in a positive correlation according to the multiple relationship between the width of the path and the radius of the robot's circumscribed circle, thereby avoiding the situation in which the robot's adjustment space is narrower due to the expansion width being too large in a narrow area, which causes the robot to need to repeatedly adjust its posture when passing through, making it difficult for the robot to pass through the narrow area. The adaptive obstacle avoidance method can adaptively reduce the expansion width of the obstacle in a narrow area to reduce the difficulty of planning the robot's obstacle avoidance path and improve the robot's adaptability to narrow spaces.

[0010] In the above-mentioned adaptive obstacle avoidance method, in the step of setting the expansion width of the obstacle according to the multiple relationship between the path width and the radius of the circumscribed circle of the robot, the expansion width Di st' is calculated by the following formula:

[0011] Dist′=K*Dist

[0012]

[0013] Where Di st is the preset default value of the expansion width, K is the adjustment coefficient, W is the path width, and R is the radius of the robot's circumscribed circle.

[0014] In the above-mentioned adaptive obstacle avoidance method, when the robot moves to the shelf to be docked, it enters the shelf docking position in the following way:

[0015] The robot uses the radar on the robot to obtain the distance between the front end of the robot and the shelf, and controls the robot to move forward according to the distance between the front end of the robot and the shelf until the distance between the robot and the shelf reaches the preset docking distance;

[0016] The distance between the two sides of the robot and the two sides of the shelf docking position is obtained through the distance measuring sensor on the side of the shelf, and the angle of the robot is adjusted according to the distance between the two sides of the robot and the two sides of the shelf docking position to keep the robot in the center of the shelf docking position.

[0017] A computer-readable storage medium stores a computer program, which, when executed and called by a processor, implements the above-mentioned adaptive obstacle avoidance method for a warehouse robot.

[0018] An adaptive obstacle avoidance control device for a warehouse robot comprises a processor and a memory, wherein the processor is electrically connected to the memory, and a computer program is stored in the memory. When the computer program is called and executed by the processor, the adaptive obstacle avoidance method for the warehouse robot is implemented.

[0019] An adaptive obstacle avoidance control device for a warehouse robot comprises: an acquisition module, used for acquiring path information of the robot and the current position of the robot; an obstacle detection module, used for detecting obstacles in a scene and identifying the size of the obstacles; an expansion width setting module, used for calculating and setting the expansion width of the obstacle according to the path width of the area in front of the robot, so that the expansion width and the path width are positively correlated within a certain range; an expansion module, used for expanding the boundary of the obstacle in the scene identified by the obstacle according to the expansion width set by the expansion width module; and an obstacle avoidance module, used for calculating an obstacle avoidance path according to the boundary of the obstacle expanded by the expansion module, and guiding the robot to avoid the obstacle according to the obstacle avoidance path.

[0020] In the above-mentioned adaptive obstacle avoidance control device, the expansion width setting module calculates the expansion width Dist' by the following formula:

[0021] Dist′=K*Dist

[0022]

[0023] Where Di st is the preset default value of the expansion width, K is the adjustment coefficient, W is the path width, and R is the radius of the robot's circumscribed circle.

[0024] In the above-mentioned adaptive obstacle avoidance control device, the acquisition module is also used to obtain the distance between the two sides of the robot and the two sides of the shelf docking position detected by the ranging sensors on both sides of the shelf docking position where the robot is docked, and to obtain the distance between the front end of the robot and the shelf.

[0025] The above-mentioned adaptive obstacle avoidance control device also includes: a docking module, which is used to control the robot to move forward according to the distance between the front end of the robot and the shelf until the distance between the robot and the shelf reaches a preset docking distance, and at the same time adjust the angle of the robot according to the distance between the two sides of the robot and the two sides of the shelf docking position, so that the robot remains in the center of the shelf docking position.

[0026] A warehousing system comprises: an AGV robot for transporting goods, provided with the above-mentioned adaptive obstacle avoidance control device of the warehouse robot, and having a radar sensor installed on the top; a plurality of shelves for temporarily storing goods, and docking distance measuring sensors are arranged on both sides of the shelf docking position of each shelf, and the docking distance measuring sensors are electrically connected to a wireless communication unit, and the wireless communication unit is used for wireless communication with the AGV robot.

[0027] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a flow chart of the adaptive obstacle avoidance method of the warehouse robot according to an embodiment of the present invention;

[0029] Figure 2 Schematic diagram of a storage system according to an embodiment of the present invention.

[0030] Description of Figure Numbers:

[0031] 100AGV robots, 110 radars, 200 shelves, 210 docking and ranging sensors. DETAILED DESCRIPTION

[0032] The embodiments of the present invention are described in detail below. Figure 1, an embodiment of the present invention provides an adaptive obstacle avoidance method for a warehouse robot, comprising the following steps:

[0033] Get the path width of the area in front of the robot;

[0034] The expansion width of the obstacle is set according to the path width of the front area, so that the expansion width and the path width are positively correlated within a certain range;

[0035] Detect the size of obstacles in the scene and expand the boundaries of the obstacles detected in the scene according to the set expansion width;

[0036] The robot is guided to avoid the obstacle according to the expanded boundary of the obstacle.

[0037] The adaptive obstacle avoidance algorithm of the embodiment of the present invention adjusts the expansion width of the obstacle in a positive correlation with the width of the front path, so that the expansion width changes positively with the width of the front path within a certain range, that is, when the path width is sufficient, the boundary of the obstacle in the detected scene is expanded with a larger expansion width, so that the robot can maintain a larger distance from the obstacle when avoiding the obstacle, reducing the probability of the robot colliding with the obstacle; when the path width is narrow, the boundary of the obstacle in the detected scene is expanded with a smaller expansion width, so as to avoid the expansion width being too large, resulting in the robot's avoidance space being too narrow, resulting in the robot's posture needing to be frequently adjusted when passing, resulting in the robot's efficiency in passing through narrow places being too slow, and the image robot's handling efficiency. The adaptive obstacle avoidance algorithm can improve the robot's ability to adapt to narrow spaces and improve the robot's efficiency in passing through narrow areas.

[0038] It is understandable that the specific adjustment margin of the expansion width can be set according to the size of the actual robot and the specific working scene. The expansion width can be calculated based on the mapping relationship between the expansion width and the multiple of the path width relative to the circumscribed circle radius of the robot. The mapping relationship can be obtained based on experience or experimental data. In this embodiment, the default value of the expansion width is set to Di st, and the actual expansion width Dist′=K*Dist, K is the adjustment coefficient belonging to [0,1], and the value of K can be calculated according to the following formula:

[0039]

[0040] That is, when the width of the front path is greater than or equal to 4 times the robot's circumcircle radius, the expansion width is set to its default value; when the width of the front path is between 2 times the robot's circumcircle radius and 4 times the robot's circumcircle radius, the adjustment coefficient K is consistent with the path width. A positively correlated linear function of the front path; when the width of the front path is less than or equal to 2 times the circumscribed circle radius of the robot, the expansion width is set to 0, and the obstacle avoidance path is planned based on the actual size of the obstacle.

[0041] In actual application scenarios, the spacing between the shelves 200 is usually less than 2 times the radius of the circumscribed circle of the robot, that is, when the robot docks with the shelf 200, the expansion width of the obstacle usually needs to be set to 0. At this time, when the robot is guided to dock with the shelf 200 only by the sensor on the robot itself, the robot is likely to collide with the shelf 200. Therefore, it is necessary to install distance measuring sensors on both sides of the shelf docking position of the shelf 200 to measure the distance between the two sides of the shelf docking position and the two sides of the robot in real time, as a basis for adjusting the robot's posture, to avoid the robot from colliding with the shelf 200 when entering and exiting the shelf docking position. In this embodiment, a laser radar 110 sensor is provided at the front end of the robot to detect the distance between the front end of the robot and the shelf 200, and the robot controls the robot to move forward and backward according to the distance between the front end and the shelf 200. Laser ranging sensors are provided on both sides of the shelf docking position to detect the distance between the two sides of the robot and the two sides of the shelf docking position, and send it to the docked robot through wireless communication. The docked robot adjusts the robot's posture according to the distance feedback from the shelf 200, guides the robot to enter or leave the shelf docking position, and completes docking and separation with the shelf 200.

[0042] It is understandable that the width of the path can be detected by the sensor on the robot, or pre-entered by humans when performing path planning. The robot's obstacle avoidance path can be calculated and generated by SLAM technology combined with obstacle avoidance algorithms such as ORCA algorithm or Bug algorithm, combined with the position of obstacles in the detected scene and the boundary expanded according to the set expansion width.

[0043] Based on the same inventive concept, an embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the above-mentioned adaptive obstacle avoidance method of the warehouse robot can be implemented.

[0044] In some possible embodiments, various aspects of the adaptive obstacle avoidance method for a warehouse robot provided by the present invention may also be implemented in the form of a program product, which includes a program code. When the program product is run on a device, the program code is used to enable the control device to execute the steps of the adaptive obstacle avoidance method according to various exemplary embodiments of the present application described above in this specification.

[0045] Based on the same inventive concept, an embodiment of the present invention also provides a control device for implementing the above-mentioned adaptive obstacle avoidance method of the warehouse robot, including a processor and a memory, the memory is electrically connected to the processor, and the processor is used to execute the computer program stored in the memory to implement the above-mentioned adaptive obstacle avoidance method of the warehouse robot.

[0046] In one possible design, the processor may include one or more processing units, and the processor may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the modem processor may not be integrated into the processor. In some embodiments, the processor and the memory may be implemented on the same chip, and in some embodiments, they may also be implemented separately on separate chips.

[0047] The processor may be a general-purpose processor, such as a central processing unit (CPU), a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, which may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the adaptive obstacle avoidance method disclosed in the embodiments of the present application may be directly embodied as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0048] As a non-volatile computer-readable storage medium, the memory can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory can include at least one type of storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (Random Access Memory, RAM), a static random access memory (Static Random Access Memory, SRAM), a programmable read-only memory (Programmab le Read On ly Memory, PROM), a read-only memory (Read On ly Memory, ROM), an electrically erasable programmable read-only memory (Electrically Erasable Programmab l eRead-Only Memory, EEPROM), a magnetic memory, a disk, an optical disk, etc. The memory is any other medium that can be used to carry or store a desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory in the embodiment of the present application can also be a circuit or any other device that can realize a storage function, for storing program instructions and / or data.

[0049] By designing and programming the processor, the code corresponding to the adaptive obstacle avoidance method for the warehouse robot described in the above embodiment can be fixed into the chip, so that the chip can execute the steps of the adaptive obstacle avoidance method for the warehouse robot in the embodiment shown in the present invention when running. How to design and program the processor is a technology well known to those skilled in the art and will not be described in detail here.

[0050] Based on the same inventive concept, an embodiment of the present invention also provides another adaptive obstacle avoidance control device for a warehouse robot, including an acquisition module, an obstacle detection module, an expansion width setting module, an expansion module and an obstacle avoidance module. The acquisition module is used to acquire the path information of the robot and the current position of the robot, and the obstacle detection module is used to detect obstacles in the scene and identify the size of the obstacles. The expansion width setting module is used to calculate and set the expansion width of the obstacle according to the path width of the area in front of the robot, so that the expansion width and the path width are positively correlated within a certain range. The expansion module is used to expand the boundaries of obstacles in the scene identified by the obstacles according to the expansion width set by the expansion width module. The obstacle avoidance module is used to calculate the obstacle avoidance path according to the boundaries of the obstacles after expansion by the expansion module, and guide the robot to avoid the obstacles according to the obstacle avoidance path.

[0051] In this embodiment, the expansion width module stores a preset expansion width default value Dist and the radius R of the robot's circumscribed circle, and calculates the adjustment coefficient K through the above formula 1 based on the multiple relationship between the path width of the front area obtained by the acquisition module and the radius of the circumscribed circle, and calculates the expansion width Dist′=K*Dist corresponding to the front path based on the calculated adjustment coefficient K.

[0052] In this embodiment, when docking with the shelf 200, the acquisition module is also used to obtain the distance between the two sides of the robot and the two sides of the shelf docking position from the distance measuring sensor on the docking position of the shelf to be docked, and obtain the distance between the front end of the robot and the shelf 200 to be docked measured in real time by the distance measuring sensor at the front end of the robot. The control device also includes a docking module, which is used to control the robot to move forward or backward according to the distance between the front end of the robot and the shelf 200 until the distance between the robot and the shelf 200 reaches a preset docking distance. At the same time, the angle of the robot is adjusted according to the distance between the two sides of the robot and the two sides of the shelf docking position, so that the robot remains in the center of the shelf docking position during the docking process with the shelf 200.

[0053] Reference Figure 2 Based on the same inventive concept, an embodiment of the present invention further provides a warehousing system, including an AGV robot 100 and a plurality of shelves 200. The AGV robot 100 is used to carry goods, and is provided with the above-mentioned adaptive obstacle avoidance control device of the warehouse robot, and a radar 110 is provided on the top, and the radar 110 is used to detect the distance between the front end of the robot and the shelf 200 when the AGV robot 100 is docked with the shelf 200. The shelf 200 is used to temporarily store goods, and docking distance measuring sensors 210 are provided on both sides of the shelf docking position of the shelf 200, and the docking distance measuring sensors 210 are used to detect the distance between the two sides of the shelf docking position and the two sides of the AGV robot 100. The docking distance measuring sensor 210 is electrically connected to the wireless communication unit, and is used to communicate with the docked AGV robot 100, and transmits the detected real-time distance between the two sides of the shelf docking position and the two sides of the AGV robot 100 to the AGV robot 100, so that the AGV robot 100 can adjust the posture of the AGV robot 100 according to the distance between its two sides and the two sides of the shelf docking position, so as to avoid the AGV robot 100 colliding with the shelf 200 when docking or separating with the shelf 200 when Dist is 0.

[0054] The present application is described with reference to the flowcharts and / or block diagrams of the methods, apparatus (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0055] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0056] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0057] In the description of the present invention, "several" means one or more, "more" means two or more, "greater than", "less than", "exceed" etc. are understood to exclude the number itself, and "above", "below", "within" etc. are understood to include the number itself. If there is a description of "first" or "second", it is only used to distinguish the technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0058] In the description of the present invention, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in the present invention based on the specific content of the technical solution.

[0059] The above-mentioned embodiments are only preferred embodiments of the present invention and cannot be used to limit the scope of protection of the present invention. Any non-substantial changes and substitutions made by technicians in this field on the basis of the present invention shall fall within the scope of protection required by the present invention.

Claims

1. An adaptive obstacle avoidance method for a warehouse robot, characterized in that: The steps include: Get the path width of the area in front of the robot; The expansion width of the obstacle is set according to the path width of the front area, so that the expansion width and the path width are positively correlated within a certain range; Detect the size of obstacles in the scene and expand the boundaries of the obstacles detected in the scene according to the set expansion width; The robot is guided to avoid the obstacle according to the expanded boundary of the obstacle.

2. The adaptive obstacle avoidance method according to claim 1, characterized in that: In the step of setting the expansion width of the obstacle in a positive correlation according to the multiple relationship between the path width and the radius of the robot's circumscribed circle, the expansion width Dist' is calculated by the following formula: Dist′=K*Dist Where Dist is the preset default value of the expansion width, K is the adjustment coefficient, W is the path width, and R is the radius of the robot's circumscribed circle.

3. The adaptive obstacle avoidance method according to claim 1, characterized in that: When the robot moves to the shelf (200) to be docked, it enters the shelf docking position in the following manner: The distance between the front end of the robot and the shelf (200) is acquired by a radar (110) on the robot, and the robot is controlled to move forward according to the distance between the front end of the robot and the shelf (200) until the distance between the robot and the shelf (200) reaches a preset docking distance; The distance between the two sides of the robot and the two sides of the docking position of the shelf (200) is obtained by a distance measuring sensor on the side of the shelf (200), and the angle of the robot is adjusted according to the distance between the two sides of the robot and the two sides of the docking position of the shelf, so that the robot remains in the center of the docking position of the shelf.

4. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed and called by the processor, the adaptive obstacle avoidance method of the warehouse robot according to any one of claims 1 to 3 is implemented.

5. An adaptive obstacle avoidance control device for a warehouse robot, characterized in that: It includes a processor and a memory, the processor is electrically connected to the memory, a computer program is stored in the memory, and when the computer program is called and executed by the processor, the adaptive obstacle avoidance method of the warehouse robot according to any one of claims 1 to 3 is implemented.

6. An adaptive obstacle avoidance control device for a warehouse robot, characterized in that: include: The acquisition module is used to obtain the path information of the robot and the current position of the robot; Obstacle detection module, used to detect obstacles in the scene and identify the size of the obstacles; An expansion width setting module is used to calculate and set the expansion width of the obstacle according to the path width of the area in front of the robot, so that the expansion width and the path width are positively correlated within a certain range; an expansion module, configured to expand the boundary of the obstacle in the scene identified by the obstacle according to the expansion width set by the expansion width module; The obstacle avoidance module is used to calculate an obstacle avoidance path according to the boundary of the obstacle expanded by the expansion module, and guide the robot to avoid the obstacle according to the obstacle avoidance path.

7. The adaptive obstacle avoidance control device according to claim 6, characterized in that: The expansion width setting module calculates the expansion width Dist' by the following formula: Dist′=K*Dist Where Dist is the preset default value of the expansion width, K is the adjustment coefficient, W is the path width, and R is the radius of the robot's circumscribed circle.

8. The adaptive obstacle avoidance control device according to claim 6, characterized in that: The acquisition module is also used to acquire the distance between the two sides of the robot and the two sides of the shelf docking position detected by the distance measuring sensors on both sides of the shelf docking position where the robot is docked, and to acquire the distance between the front end of the robot and the shelf (200).

9. The adaptive obstacle avoidance control device according to claim 8, characterized in that: Also includes: The docking module is used to control the robot to move forward according to the distance between the front end of the robot and the shelf (200) until the distance between the robot and the shelf (200) reaches a preset docking distance, and at the same time adjust the angle of the robot according to the distance between the two sides of the robot and the two sides of the shelf docking position, so that the robot remains in the center of the shelf docking position.

10. A storage system, characterized in that: include: An AGV robot (100) for transporting goods, provided with an adaptive obstacle avoidance control device for a warehouse robot according to any one of claims 5 to 9, and provided with a radar (110) on the top; A plurality of shelves (200) are used for temporarily storing goods, and docking distance measuring sensors (210) are provided on both sides of the shelf docking position of each shelf (200), and the docking distance measuring sensors (210) are electrically connected to a wireless communication unit, and the wireless communication unit is used for wireless communication with the AGV robot (100).

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