Warehouse robot adaptive obstacle avoidance control method and device and storage medium

Abstract

The application relates to the technical field of intelligent storage, and discloses a warehouse robot self-adaptive obstacle avoidance method and device and a storage medium, wherein the method comprises the following steps: acquiring the path width of the front area of the robot; setting the inflation width of the obstacle according to the path width of the front area, so that the inflation width and the path width are positively correlated within a certain range; detecting the size of the obstacle in the scene, and inflating the boundary of the detected obstacle in the scene according to the set inflation width; and guiding the robot to avoid the obstacle according to the boundary of the inflated obstacle. According to the obstacle avoidance method, the inflation width is adaptively set according to the path width in front, so that when passing through a narrow area, the inflation width is not too large, the posture adjustment range of the robot during obstacle avoidance is not too narrow, and the robot does not need to spend a large amount of time in adjusting the posture when passing through the narrow area due to the too large inflation width, so that the adaptability to the narrow area can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent warehousing, in particular to a warehouse robot adaptive obstacle avoidance control method and device and storage medium. BACKGROUND

[0002] With the development of automatic navigation technology, more and more logistics warehouses and factories begin to use AGV robots to complete the transportation of goods, products and production materials. In order to avoid collision between the robot and the obstacle during operation, in the SLAM navigation technology, a distance is usually set for the detected obstacle to prevent the robot from being too close to the obstacle. In the existing robot navigation scheme, the value of Dist is fixed, which will cause the robot to spend a lot of time adjusting the attitude of the robot when passing through a narrow area, and the adaptability of the robot is poor, which is difficult to adapt to the warehouse in the factory with limited space and dense shelves, such as lithium battery warehouse. SUMMARY

[0003] In order to overcome the shortcomings of the prior art, the purpose of the present application is to provide a warehouse robot adaptive obstacle avoidance, which can adjust the inflation width of the obstacle in real time according to the path width, reduce the difficulty of the robot passing through a narrow area, and improve the adaptability of the robot to narrow space.

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

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

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

[0007] Detect the size of the obstacle in the scene, and inflate the boundary of the detected obstacle in the scene according to the set inflation width;

[0008] Guide the robot to avoid the obstacle according to the boundary of the inflated obstacle.

[0009] Compared with the prior art, the present application has the beneficial effects that by positively correlating the inflation width of the obstacle according to the multiple relationship between the width of the path and the radius of the circumscribed circle of the robot, the inflation width of the obstacle is adjusted, so as to avoid that when passing through a narrow area, the inflation width is too large, which will cause the adjustment space of the robot to be narrower, and thus the robot needs to repeatedly adjust the attitude of the robot when passing through, which will cause the robot to be difficult to pass through the narrow area. The adaptive obstacle avoidance method can adaptively reduce the inflation width of the obstacle in the narrow area, so as to reduce the planning difficulty of the obstacle avoidance path of the robot and improve the adaptability of the robot to narrow space.

[0010] In the aforementioned adaptive obstacle avoidance method, the step of setting the obstacle's expansion width based on the positive correlation between the path width and the robot's circumcircle radius is used to calculate the expansion width Di st' using the following formula:

[0011] Dist′=K*Dist

[0012]

[0013] In the formula, 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 outer circle.

[0014] The adaptive obstacle avoidance method described above allows the robot to enter the docking position at the shelf where it needs to dock, in the following manner:

[0015] The distance between the robot's front end and the shelf is obtained by the radar on the robot, and the robot is controlled to move forward according to the distance between the robot's front end and the shelf until the distance between the robot and the shelf reaches the preset docking distance.

[0016] The distance between the robot's two sides and the two sides of the shelf docking position is obtained by the distance measuring sensor on the side of the shelf, and the robot's angle is adjusted according to the distance between the robot's two sides 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 storing a computer program, which, when executed by a processor, implements the aforementioned adaptive obstacle avoidance method for a warehouse robot.

[0018] An adaptive obstacle avoidance control device for a warehouse robot includes a processor and a memory. The processor is electrically connected to the memory, and the memory stores a computer program. When the computer program is called and executed by the processor, it implements the aforementioned adaptive obstacle avoidance method for the warehouse robot.

[0019] An adaptive obstacle avoidance control device for a warehouse robot includes: an acquisition module for acquiring the robot's path information and current position; an obstacle detection module for detecting obstacles in the scene and identifying their dimensions; an expansion width setting module for calculating and setting the expansion width of the obstacles based on the path width in front of the robot, such that the expansion width and path width are positively correlated within a certain range; an expansion module for expanding the boundaries of the obstacles in the scene detected by the obstacle detection module according to the expansion width set by the expansion width module; and an obstacle avoidance module for calculating an obstacle avoidance path based on the expanded boundary of the obstacles by the expansion module, and guiding the robot to avoid obstacles according to the obstacle avoidance path.

[0020] In the aforementioned adaptive obstacle avoidance control device, the expansion width setting module calculates the expansion width Dist' using the following formula:

[0021] Dist′=K*Dist

[0022]

[0023] In the formula, 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 outer circle.

[0024] In the aforementioned adaptive obstacle avoidance control device, the acquisition module is further used to acquire 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, and to acquire the distance between the front end of the robot and the shelf.

[0025] The aforementioned adaptive obstacle avoidance control device also includes a docking module, which controls the robot to move forward based on 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 simultaneously adjusts the robot's angle based on 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 includes: an AGV robot for transporting goods, equipped with an adaptive obstacle avoidance control device for the aforementioned warehouse robot, and a radar sensor mounted on its top; multiple shelves for temporarily storing goods, each shelf having a docking distance sensor on both sides of its docking position, the docking distance sensor being electrically connected to a wireless communication unit, the wireless communication unit being used for wireless communication with the AGV robot.

[0027] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments. Attached Figure Description

[0028] Figure 1 This is a flowchart of an adaptive obstacle avoidance method for a warehouse robot according to an embodiment of the present invention;

[0029] Figure 2 This is a schematic diagram of a warehousing system according to an embodiment of the present invention.

[0030] Explanation of icon numbers:

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

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

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

[0034] The expansion width of obstacles is set according to the path width of the area ahead, 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 detected obstacles according to the set expansion width;

[0036] The robot is guided to avoid obstacles based on the boundaries of the expanded obstacles.

[0037] The adaptive obstacle avoidance algorithm of this invention adjusts the expansion width of obstacles in a positive correlation with the width of the path ahead. This expansion width varies positively with the path width within a certain range. Specifically, when the path width is sufficient, a larger expansion width is used to expand the boundaries of detected obstacles in the scene, allowing the robot to maintain a greater distance from obstacles and reducing the probability of collision. When the path width is narrow, a smaller expansion width is used to expand the boundaries of detected obstacles in the scene. This avoids excessive expansion width that would narrow the robot's avoidance space, requiring frequent adjustments to the robot's posture and resulting in slow passage through narrow areas, thus affecting the robot's carrying efficiency. This adaptive obstacle avoidance algorithm improves the robot's adaptability to narrow spaces and increases its efficiency in navigating narrow areas.

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

[0039]

[0040] When the width of the current path is greater than or equal to four times the robot's circumcircle radius, the expansion width is set to its default value; when the width of the current path is between two and four times the robot's circumcircle radius, the adjustment coefficient K conforms to the path width. The positively correlated linear function; when the width of the current path is less than or equal to twice the radius of the robot's outer circle, the expansion width is set to 0, and the obstacle avoidance path is planned based on the actual size of the obstacle.

[0041] In practical applications, the distance between shelves 200 is usually less than twice the radius of the robot's circumscribed circle. This means that when the robot docks with the shelf 200, the obstacle's expansion width usually needs to be set to zero. If only the robot's own sensors guide the docking, collisions are likely. Therefore, distance sensors need to be installed on both sides of the docking position to measure the distance between the robot and the shelf 200 in real time. This distance serves as the basis for adjusting the robot's posture and preventing collisions when the robot enters or leaves the docking position. In this embodiment, a LiDAR 110 sensor is installed at the front of the robot to detect the distance between the robot's front and the shelf 200. The robot controls its forward and backward movement based on this distance. Laser distance sensors are installed on both sides of the shelf docking position to detect the distance between the robot's sides and the shelf docking position. This distance is transmitted wirelessly to the docking robot. The docking robot adjusts its posture based on the distance feedback from the shelf 200, guiding it into or out of the docking position to complete docking and separation from the shelf 200.

[0042] Understandably, the path width can be obtained by sensors on the robot or pre-input by a human during path planning. The robot's obstacle avoidance path can be calculated and generated by combining SLAM technology with obstacle avoidance algorithms such as ORCA or Bug algorithms, taking into account the positions of detected obstacles in the scene and the boundary after expansion based on the set expansion width.

[0043] Based on the same inventive concept, embodiments of the present invention also provide a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the aforementioned adaptive obstacle avoidance method for warehouse robots.

[0044] In some possible implementations, various aspects of the adaptive obstacle avoidance method for warehouse robots provided by the present invention can also be implemented in the form of a program product, which includes program code that, when the program product is run on a device, causes the control device to perform the steps in the adaptive obstacle avoidance method according to the various exemplary embodiments of the present application described above.

[0045] Based on the same inventive concept, embodiments of the present invention also provide a control device for implementing the above-described adaptive obstacle avoidance method for a warehouse robot, including a processor and a memory, wherein the memory is electrically connected to the processor, and the processor implements the above-described adaptive obstacle avoidance method for a warehouse robot by executing a computer program stored in the memory.

[0046] In one possible design, the processor may include one or more processing units. The processor may integrate an application processor and a modem processor, wherein the application processor primarily handles the operating system, user interface, and applications, while the modem processor primarily handles wireless communication. It is understood that the modem processor may also not be integrated into the processor. In some embodiments, the processor and memory may be implemented on the same chip; in some embodiments, they may also be implemented on separate chips.

[0047] The processor can be a general-purpose processor, such as a central processing unit (CPU), digital signal processor, application-specific integrated circuit, field-programmable gate array or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the adaptive obstacle avoidance method disclosed in the embodiments of this application can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0048] Memory, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory can include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic memory, magnetic disk, optical disk, etc. Memory is any other medium capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer, but is not limited to this. The memory in the embodiments of this application can also be a circuit or any other device capable of implementing storage functions for storing program instructions and / or data.

[0049] By designing and programming the processor, the code corresponding to the adaptive obstacle avoidance method of the warehouse robot described in the foregoing embodiments can be embedded into the chip, thereby enabling the chip to execute the steps of the adaptive obstacle avoidance method of the warehouse robot shown in the embodiments of the present invention during operation. How to design and program the processor is a technique well known to those skilled in the art, and will not be elaborated here.

[0050] Based on the same inventive concept, embodiments of the present invention also provide 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 acquires the robot's path information and its current position. The obstacle detection module detects obstacles in the scene and identifies their dimensions. The expansion width setting module calculates and sets the expansion width of the obstacles based on the path width in front of the robot, ensuring a positive correlation between the expansion width and the path width within a certain range. The expansion module expands the boundaries of the obstacles identified in the scene according to the expansion width set by the expansion width module. The obstacle avoidance module calculates an obstacle avoidance path based on the expanded obstacle boundaries and guides the robot to avoid obstacles according to the path.

[0051] In this embodiment, the expansion width module stores a preset default expansion width Dist and the radius R of the robot's circumcircle. Based on the multiple relationship between the path width of the front area and the radius of the circumcircle obtained by the acquisition module, the adjustment coefficient K is calculated using Equation 1 above. Based on the calculated adjustment coefficient K, the expansion width Dist′ = K * Dist corresponding to the front path is calculated.

[0052] In this embodiment, when the acquisition module docks with the shelf 200, it is also used to acquire 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 200, as needed based on the position of the shelf 200 to be docked, and to acquire the distance between the front end of the robot and the shelf 200 to be docked, as measured in real time by the distance measuring sensor. The control device also includes a docking module, 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 the preset docking distance. At the same time, it adjusts 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 during the docking process.

[0053] Reference Figure 2 Based on the same inventive concept, embodiments of the present invention also provide a warehousing system, including an AGV robot 100 and multiple shelves 200. The AGV robot 100 is used for transporting goods and is equipped with the aforementioned adaptive obstacle avoidance control device for warehouse robots. A radar 110 is mounted on its top, which is used to detect the distance between the front end of the AGV robot 100 and the shelf 200 when the AGV robot 100 docks with the shelf 200. The shelf 200 is used for temporarily storing goods, and docking distance sensors 210 are mounted on both sides of the shelf docking position of the shelf 200. The docking distance 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 sensor 210 is electrically connected to the wireless communication unit for communicating with the docking AGV robot 100. It transmits the real-time distances between the two sides of the docking position of the shelf and the two sides of the AGV robot 100 to the AGV robot 100 so that the AGV robot 100 can adjust its posture according to the distances between its two sides and the docking position of the shelf. This prevents the AGV robot 100 from colliding with the shelf 200 when the Dist value is 0.

[0054] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0055] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0056] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0057] In the description of this invention, "several" means one or more, "more than" means two or more, "greater than," "less than," "exceeding," etc. are understood to exclude the stated number, while "above," "below," "within," etc. are understood to include the stated number. If "first" or "second" is mentioned, it is only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0058] In the description of this invention, unless otherwise explicitly defined, terms such as "setting," "installing," and "connecting" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this invention in conjunction with the specific content of the technical solution.

[0059] The above embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of protection of the present invention. Any non-substantial changes and substitutions made by those skilled in the art based on the present invention shall fall within the scope of protection claimed by the present invention.

Claims

1. An adaptive obstacle avoidance method for a warehouse robot, characterized in that, Includes the following steps: Obtain the path width of the area in front of the robot; The expansion width of obstacles is set according to the path width of the area ahead, 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 detected obstacles according to the set expansion width; The robot is guided to avoid obstacles based on the boundaries of the expanded obstacles; In the step of setting the obstacle's expansion width based on the positive correlation between the path width and the robot's circumscribed circle radius, the expansion width Dist' is calculated using the following formula: In the formula, Dist is the 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 outer circle.

2. The adaptive obstacle avoidance method according to claim 1, characterized in that, When the robot moves to the shelf (200) that needs to be docked, it enters the docking position of the shelf in the following manner: The distance between the front end of the robot and the shelf (200) is obtained by the 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 the preset docking distance. The distance between the two sides of the robot and the two sides of the shelf docking position is obtained by the distance 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 shelf docking position so that the robot is kept in the center of the shelf docking position.

3. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed and called by the processor, it implements the adaptive obstacle avoidance method for the warehouse robot according to claim 1 or 2.

4. An adaptive obstacle avoidance control device for a warehouse robot, characterized in that, It includes a processor and a memory, the processor being electrically connected to the memory, the memory storing a computer program, which, when executed by the processor, implements the adaptive obstacle avoidance method for the warehouse robot according to claim 1 or 2.

5. An adaptive obstacle avoidance control device for a warehouse robot, characterized in that, include: The acquisition module is used to acquire the robot's path information and its current location; 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 obstacles based on 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 is used to expand the boundaries of obstacles within 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 the obstacle avoidance path based on the boundary of the obstacle after the expansion module expands, and guide the robot to avoid the obstacle based on the obstacle avoidance path; The expansion width setting module calculates the expansion width Dist' using the following formula: In the formula, Dist is the 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 outer circle.

6. The adaptive obstacle avoidance control device according to claim 5, 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, and to acquire the distance between the front end of the robot and the shelf (200).

7. The adaptive obstacle avoidance control device according to claim 6, 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 the 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 docking position of the shelf, so that the robot stays in the center of the docking position of the shelf.

8. A warehousing system, characterized in that, include: An AGV robot (100) for transporting goods is equipped with an adaptive obstacle avoidance control device for a warehouse robot according to any one of claims 4-7, and a radar (110) is provided on its top. Multiple shelves (200) are used for temporary storage of goods. Each shelf (200) has a docking distance sensor (210) on both sides of the docking position. The docking distance sensor (210) is electrically connected to a wireless communication unit, which is used to communicate wirelessly with the AGV robot (100).

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