A robot control method and system for automatic operation in complex road conditions

Abstract

The present disclosure provides a robot control method and system for automatically operating in complex road conditions, belonging to the field of intelligent control. The method includes: determining road condition classification information of a target area based on environmental perception information of the target area; the target area is the current operating area of the target robot; determining the category of the target area based on the road condition classification information; in response to the category of the target area changing from a first category to a second category, switching the robot's control parameters from a first parameter value to a second parameter value; the first parameter value is the parameter value corresponding to the first category, and the second parameter value is the parameter value corresponding to the second category; and controlling the operation of the target robot based on the control parameters. The robot control method and system for automatically operating in complex road conditions provided by the present disclosure can reduce the computational complexity of the mobile robot.

Description

Technical Field

[0001] The present disclosure belongs to the field of intelligent control technology, and more specifically, relates to a robot control method and system for automatic operation under complex road conditions. Background Art

[0002] Mobile robots can assist or replace humans in various tasks. For example, in automobile manufacturing, mobile robots can move parts from one work area to another, automating production. In exploration, mobile robots can enter narrow spaces underground, carrying sensors and cameras to inspect mineral veins and obtain information on the quality and distribution of mineral deposits. This not only saves labor costs but also improves efficiency and the working environment.

[0003] During operation, mobile robots may encounter various complex road conditions such as slopes and steps. In order to adapt to the changes in various road conditions, a large amount of calculations are required inside the mobile robot. The large amount of calculations will bring about a series of problems such as high power consumption and slow response speed. Summary of the Invention

[0004] The purpose of the present disclosure is to provide a robot control method and system for automatic operation in complex road conditions, so as to reduce the computational complexity of the mobile robot.

[0005] A first aspect of the embodiments of the present disclosure provides a method for controlling a robot that automatically operates in complex road conditions, comprising:

[0006] Determining road condition classification information of the target area based on environmental perception information of the target area; the target area is the current operating area of the target robot;

[0007] determining a category of a target area based on the road condition classification information;

[0008] In response to the category of the target area changing from the first category to the second category, switching a control parameter of the robot from a first parameter value to a second parameter value;

[0009] The first parameter value is a parameter value corresponding to the first category, and the second parameter value is a parameter value corresponding to the second category;

[0010] The operation of the target robot is controlled based on the control parameters.

[0011] A second aspect of the embodiments of the present disclosure provides a robot control device for automatically operating in complex road conditions, comprising:

[0012] A first classification module is configured to determine road condition classification information of a target area based on environmental perception information of the target area; the target area is a current operating area of the target robot;

[0013] a second classification module, configured to determine a category of a target area based on the road condition classification information;

[0014] a parameter switching module, configured to switch a control parameter of the robot from a first parameter value to a second parameter value in response to a change in the category of the target area from the first category to the second category;

[0015] The first parameter value is a parameter value corresponding to the first category, and the second parameter value is a parameter value corresponding to the second category;

[0016] The control output module is used to control the operation of the target robot based on the control parameters.

[0017] According to a third aspect of an embodiment of the present disclosure, a robot controller is provided, comprising a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of the above-mentioned method for controlling a robot that automatically operates in complex road conditions are implemented.

[0018] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned method for controlling a robot that automatically operates in complex road conditions are implemented.

[0019] The beneficial effects of the robot control method and system for automatic operation in complex road conditions provided by the embodiments of the present disclosure are:

[0020] In the embodiment of the present disclosure, considering that the robot will have different control parameters under different road condition classification information, and the robot will repeat work along the same operation route during operation, typical control parameters under various road condition classifications can be collected in advance as control parameters corresponding to each road condition classification information. At the same time, the target area is classified based on the road condition classification information, and the control parameters corresponding to each road condition classification information are used as control parameters corresponding to the corresponding target area category.

[0021] During the actual operation of the robot, sensors can be used to obtain environmental perception information of the target area, determine road condition classification information based on the environmental perception information, and then determine control parameters corresponding to the target area based on the road condition classification information; as the robot runs, if the road condition classification information of the target area judged based on the environmental perception information changes, the category of the target area will change accordingly. For example, when the category of the target area changes from the first category to the second category, the second parameter value corresponding to the second category can be used as the control parameter of the robot to control the operation of the robot.

[0022] The disclosed embodiment divides the robot's operating area into multiple categories based on road condition classification information. During the operation of the robot, corresponding control parameters are determined according to the category of each target area. The control parameters corresponding to each target area category can be obtained based on historical data without the need for complex calculations. Therefore, the method of this embodiment can reduce the amount of calculation during the operation of the robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0024] Figure 1 A flowchart of a robot control method for automatic operation in complex road conditions provided by one embodiment of the present disclosure;

[0025] Figure 2 This is a structural block diagram of a robot control device for automatic operation in complex road conditions provided by one embodiment of the present disclosure;

[0026] Figure 3 A schematic block diagram of a robot controller provided in accordance with an embodiment of the present disclosure. DETAILED DESCRIPTION

[0027] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present disclosure. However, it will be apparent to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present disclosure with unnecessary detail.

[0028] In order to make the purpose, technical solutions and advantages of the present disclosure more clear, specific embodiments will be described below with reference to the accompanying drawings.

[0029] Please refer to Figure 1 , Figure 1 A flowchart of a method for controlling a robot that automatically operates in complex road conditions is provided in accordance with an embodiment of the present disclosure. The method includes:

[0030] S101: Determine road condition classification information of a target area based on environmental perception information of the target area; the target area is an operating area of a target robot.

[0031] In this embodiment, the environmental perception information of the target area can be obtained through detection by various sensors. By analyzing various perception information, the robot can perceive the information of the surrounding environment and realize automatic walking and navigation.

[0032] For example, the image information of the target area can be obtained through the camera, and the three-dimensional point cloud data of the target area can be obtained through the lidar. Based on the image information of the target area, the robot's operating environment information (including road information, obstacle information, etc.) can be extracted. Based on the three-dimensional point cloud data of the target area, accurate obstacle distance measurement and operating speed detection can be performed.

[0033] According to the above road surface information, road condition classification information can be obtained, and the road condition classification information can include multiple road condition classifications such as flat road surface, stepped road surface, uphill, downhill, etc.

[0034] S102: Determine the category of the target area based on the road condition classification information.

[0035] In this embodiment, considering that the robot will have different control parameters under different road condition classifications, in order to achieve smooth operation under various road condition categories, and at the same time, the robot will repeat work along the same operation route during operation, typical control parameters under various road condition classifications can be collected in advance as the control parameters corresponding to each road condition classification information. At the same time, the target area is classified based on the road condition classification information, and the control parameters corresponding to each road condition classification information are used as the control parameters corresponding to the corresponding target area category.

[0036] S103 : In response to the category of the target area being changed from the first category to the second category, switching the control parameter of the robot from the first parameter value to the second parameter value.

[0037] The first parameter value is a parameter value corresponding to the first category, and the second parameter value is a parameter value corresponding to the second category.

[0038] During the actual operation of the robot, sensors can be used to obtain environmental perception information of the target area, determine road condition classification information based on the environmental perception information, and then determine control parameters corresponding to the target area based on the road condition classification information; as the robot runs, if the road condition classification information of the target area judged based on the environmental perception information changes, the category of the target area will change accordingly. For example, when the category of the target area changes from the first category to the second category, the second parameter value corresponding to the second category can be used as the control parameter of the robot to control the operation of the robot.

[0039] S104: Controlling the operation of the target robot based on the control parameters.

[0040] In this embodiment, a controller is provided inside the robot. After the control parameters of the robot are adjusted according to the change of the target area category, the adjusted control parameters can be input into the controller to control the robot to operate with the adjusted control parameters.

[0041] From the above, it can be concluded that the embodiment of the present disclosure divides the robot's operating area into multiple categories based on road condition classification information. During the operation of the robot, the corresponding control parameters are determined according to the category of each target area. The control parameters corresponding to each target area category can be obtained based on historical data without the need for complex calculations. Therefore, the method of this embodiment can reduce the amount of calculation during the operation of the robot.

[0042] In one embodiment of the present disclosure, switching a control parameter of a robot from a first parameter value to a second parameter value includes:

[0043] In response to the control parameter belonging to a first type of control parameter, the control parameter is switched from a first parameter value to a second parameter value; the first type of control parameter is a control parameter other than a motor operation control parameter.

[0044] In response to the control parameter belonging to the second type of control parameter, the first parameter value is sequentially transformed into multiple third parameter values with a first step length, and the multiple third parameter values are sequentially determined as control parameters; the second type of control parameter is the control parameter of the motor operation.

[0045] In this embodiment, the first type of control parameters may include control cycle, movement mode, posture, etc., wherein the control cycle is the calculation cycle of the robot control instructions. The smaller the control cycle, the more precise the control of the robot; the movement mode includes wheeled operation or legged operation. The wheeled operation mode realizes the movement of the robot based on the rolling of the wheels, and has a faster movement speed and higher operation efficiency. However, the obstacle passing ability of the wheeled operation mode is poor. The legged operation mode adopts leg-type walking, including walking, jumping and running. It has low requirements for terrain and can adapt to complex terrain, but its operation speed and efficiency are usually not as good as wheeled robots; posture includes the position and posture of the robot. When the robot runs under different road conditions, its center of gravity may change. Therefore, it is necessary to adjust the position and posture of each component in time to maintain the balance of the robot.

[0046] When the first type of control parameters are quickly switched from one state to another, the stable operation of the robot will not be affected. Therefore, when the target area category is switched from the first category to the second category, the first type of control parameters can be directly switched from the first parameter value to the second parameter value.

[0047] For example, when the robot is running on a flat road area, since the control of the flat road area is relatively simple, a larger control cycle can be adopted, and a wheeled operation mode can be adopted to increase the operation speed. As the robot runs, when the target area changes from a flat road area to a stepped road area, in order to maintain the stability of the robot, the control cycle needs to be quickly reduced to achieve more precise control, and the movement mode needs to be quickly switched to a leg-type operation mode to achieve stable operation in the stepped road area.

[0048] The second category of control parameters can include operating speed, output power, and other parameters. Sudden changes in these control parameters will affect the robot's stable operation. Therefore, when the target area category switches from the first category to the second category, the first parameter value needs to be slowly adjusted to the second parameter value. Specifically, based on the first parameter value, one first step length, two first step lengths, and so on, can be adjusted, until the second parameter value is reached. The multiple third parameter values obtained from this process are used as the robot's control parameters.

[0049] For example, when the robot is operating on a flat surface, it can use wheeled operation for rapid movement. However, when the target area changes from a flat surface to a stepped surface, a lower operating speed is required. To ensure smooth operation, the operating speed needs to be gradually reduced. Another example is when the robot is climbing a slope, more power is needed to overcome gravity and friction, so the motor power output needs to be increased. To ensure smooth operation, the motor power output needs to be gradually increased.

[0050] In one embodiment of the present disclosure, the environmental perception information is image information of the target area, and determining the road condition classification information of the target area based on the environmental perception information of the target area includes:

[0051] Perform image recognition on the image of the target area to obtain an image recognition result.

[0052] Determine road condition classification information based on the image recognition results.

[0053] In this embodiment, a specific implementation method for determining road condition classification information based on environmental perception information is provided. By performing image recognition on an image of a target area, the road surface image in the image can be classified to obtain road condition classification information.

[0054] In one embodiment of the present disclosure, a method for controlling a robot that automatically operates in complex road conditions further includes:

[0055] In response to a pedestrian flow in the target area being greater than a flow threshold, a control parameter of the target robot is adjusted based on the pedestrian flow.

[0056] In this embodiment, considering that the flow of people in the target area is large, the robot needs more sophisticated navigation and obstacle avoidance control. At the same time, when the flow of people is large, in order to avoid the robot causing interference or safety threats to the staff, the robot's operating speed needs to be appropriately reduced.

[0057] Based on this, a flow threshold can be set. When the flow of people in the target area is greater than the flow threshold, the robot's control cycle is reduced to achieve more precise navigation and obstacle avoidance control; at the same time, the robot's running speed is reduced to reduce the risk of collision.

[0058] In one embodiment of the present disclosure, a method for controlling a robot that automatically operates in complex road conditions further includes:

[0059] In response to the category of the target area being the third category, an average running speed of the target robot within the first time period is calculated.

[0060] In response to an average running speed of the target robot being less than a first speed threshold, a space occupancy rate of the target area is calculated based on environmental perception information of the target area.

[0061] In response to the spatial occupancy rate of the target area being greater than the first threshold, the category of the target area is switched to the fourth category; the control parameter of the robot is switched from the third parameter value to the fourth parameter value; the third parameter value is the parameter value corresponding to the third category, and the fourth parameter value is the parameter value corresponding to the fourth category.

[0062] The third category is used to indicate that the road surface of the target area is flat, and the fourth category is used to indicate that the road surface of the target area is narrow; the space occupancy rate of the target area is used to indicate the degree of restriction of the target robot's movement in the target area.

[0063] In this embodiment, when the robot runs on a flat road, it usually runs at a higher speed. If there is construction or debris piled up in the flat road area for a period of time, the robot's moving space will be reduced, resulting in a lower running speed and an increased risk of collision.

[0064] To address this issue, this embodiment calculates the robot's average operating speed on flat roads. If the robot's average operating speed on flat roads is low (less than a first speed threshold), it indicates that construction or debris may be occurring in the target area. The target area's spatial occupancy rate can then be further calculated. If the target area's spatial occupancy rate exceeds the first threshold, construction or debris accumulation can be confirmed. The target area is then marked as a narrow area (i.e., the fourth category). The robot's operation is controlled based on the fourth parameter value corresponding to the fourth category to adapt to changes in the target area's spatial occupancy rate.

[0065] The robot's running speed can be detected in real time by using a laser radar, and the robot's real-time running speed in the first time can be added up and the average value calculated to obtain the robot's average running speed in the first time.

[0066] When it is detected that the average running speed of the robot in the first time is relatively low, the space occupancy rate of the target area can be further calculated through environmental perception information. Specifically, the road width of the target area can be obtained based on the image information of the target area, and the ratio of the robot width to the road width can be calculated to obtain the space occupancy rate of the target area.

[0067] This embodiment detects the change of the target area from a flat road area to a narrow road area based on the average running speed of the target robot on a flat road and the spatial occupancy rate of the target area, and then switches the corresponding control parameters based on the change of the target area, thereby further improving the control effect of the target robot.

[0068] Among them, the running speed of the target robot is a parameter that needs to be monitored in real time during the operation of the target robot, while the space occupancy rate of the target area does not need to be monitored in real time. Monitoring the space occupancy rate of the target area when an abnormal running speed is detected can further reduce the amount of calculation.

[0069] It should be noted that, considering that the robot's control is relatively precise when running on other roads such as steps, uphill and downhill roads, and can cope with changes in narrow spaces, this embodiment only considers changes in narrow spaces when the robot runs on flat roads.

[0070] In one embodiment of the present disclosure, a method for controlling a robot that automatically operates in complex road conditions further includes:

[0071] In response to the category of the target area being the fourth category and the height of the obstacle being less than the height threshold, the obstacle avoidance mode of the target robot is set to the first obstacle avoidance mode, and in the first obstacle avoidance mode, the target robot is controlled to cross the obstacle.

[0072] In this embodiment, when the robot encounters an obstacle during operation, it can choose to either step over it or go around it. Considering the limited space for detours on narrow roads, the computational complexity and runtime are significant. Therefore, when operating on narrow roads, the robot can prioritize stepping over obstacles. Specifically, a height threshold can be set. When the obstacle's height is below the threshold, the robot can switch to leg-based movement to step over the obstacle.

[0073] In one embodiment of the present disclosure, a method for controlling a robot that automatically operates in complex road conditions further includes:

[0074] In response to the category of the target area being the fourth category, an average running speed of the target robot within the first time period is calculated.

[0075] In response to the average running speed of the target robot being greater than a second speed threshold, a space occupancy rate of the target area is calculated based on the environmental perception information of the target area.

[0076] In response to the space occupancy rate of the target area being less than the second threshold, the category of the target area is switched to the third category; the third category is used to indicate that the road surface of the target area is a flat road surface, and the fourth category is used to indicate that the road surface of the target area is a narrow road surface; the space occupancy rate of the target area is used to indicate the degree of restriction of the target robot's movement in the target area.

[0077] The control parameter of the robot is switched from the third parameter value to the fourth parameter value; the third parameter value is the parameter value corresponding to the third category, and the fourth parameter value is the parameter value corresponding to the fourth category.

[0078] In this embodiment, if the robot's average operating speed during the first period is detected to be high (greater than the second speed threshold), it indicates that construction in the target area may have been completed or debris has been cleared. The target area's spatial occupancy rate can then be further calculated. If the target area's spatial occupancy rate falls below the second threshold, construction in the target area can be confirmed to be complete or debris has been cleared. The target area is then re-labeled as a flat road area (i.e., the third category). The robot's operation is then controlled based on the third parameter value corresponding to the third category to improve its operating speed and efficiency.

[0079] The space occupancy rate of the target area can be further calculated through environmental perception information. Specifically, the road width of the target area can be obtained based on the image information of the target area, and the ratio of the robot width to the road width can be calculated to obtain the space occupancy rate of the target area.

[0080] Corresponding to the above embodiment, a robot control method for automatic operation in complex road conditions is provided. Figure 2 This is a block diagram of a robot control device that automatically operates in complex road conditions according to an embodiment of the present disclosure. For ease of illustration, only the parts related to the embodiment of the present disclosure are shown. Figure 2 The robot control device 20 that automatically operates under complex road conditions includes: a first classification module 21, a second classification module 22, a parameter switching module 23 and a control output module 24.

[0081] The first classification module 21 is configured to determine the road condition classification information of the target area based on the environmental perception information of the target area; the target area is the current operating area of the target robot;

[0082] The second classification module 22 is configured to determine the category of the target area based on the road condition classification information.

[0083] The parameter switching module 23 is configured to switch the control parameter of the robot from a first parameter value to a second parameter value in response to the category of the target area changing from the first category to the second category.

[0084] The first parameter value is a parameter value corresponding to the first category, and the second parameter value is a parameter value corresponding to the second category.

[0085] The control output module 24 is used to control the operation of the target robot based on the control parameters.

[0086] In one embodiment of the present disclosure, the parameter switching module 23 is specifically configured to:

[0087] In response to the control parameter belonging to a first type of control parameter, the control parameter is switched from a first parameter value to a second parameter value; the first type of control parameter is a control parameter other than the motor operation control parameter.

[0088] In response to the control parameter belonging to the second type of control parameter, the first parameter value is sequentially transformed into multiple third parameter values with a first step length, and the multiple third parameter values are sequentially determined as control parameters; the second type of control parameter is the control parameter of the motor operation.

[0089] In one embodiment of the present disclosure, the first classification module 21 is specifically configured to:

[0090] Perform image recognition on the image of the target area to obtain an image recognition result.

[0091] Determine the traffic classification information of the target area based on the image recognition results.

[0092] In one embodiment of the present disclosure, the parameter switching module 23 is further configured to:

[0093] In response to a pedestrian flow in the target area being greater than a flow threshold, a control parameter of the target robot is adjusted based on the pedestrian flow.

[0094] In one embodiment of the present disclosure, the second classification module 22 is specifically configured to:

[0095] In response to the category of the target area being the third category, an average running speed of the target robot within the first time period is calculated.

[0096] In response to an average running speed of the target robot being less than a first speed threshold, a space occupancy rate of the target area is calculated based on environmental perception information of the target area.

[0097] In response to the spatial occupancy rate of the target area being greater than the first threshold, the category of the target area is switched to the fourth category; the control parameter of the robot is switched from the third parameter value to the fourth parameter value; the third parameter value is the parameter value corresponding to the third category, and the fourth parameter value is the parameter value corresponding to the fourth category.

[0098] The third category is used to indicate that the road surface of the target area is flat, and the fourth category is used to indicate that the road surface of the target area is narrow; the space occupancy rate of the target area is used to indicate the degree of restriction of the target robot's movement in the target area.

[0099] In one embodiment of the present disclosure, the second classification module 22 is further configured to:

[0100] In response to the category of the target area being the fourth category and the height of the obstacle being less than the height threshold, the obstacle avoidance mode of the target robot is set to the first obstacle avoidance mode, and in the first obstacle avoidance mode, the target robot is controlled to cross the obstacle.

[0101] In one embodiment of the present disclosure, the second classification module 22 is further configured to:

[0102] In response to the category of the target area being the fourth category, an average running speed of the target robot within the first time period is calculated.

[0103] In response to the average running speed of the target robot being greater than a second speed threshold, a space occupancy rate of the target area is calculated based on the environmental perception information of the target area.

[0104] In response to the space occupancy rate of the target area being less than the second threshold, the category of the target area is switched to the third category; the third category is used to indicate that the road surface of the target area is a flat road surface, and the fourth category is used to indicate that the road surface of the target area is a narrow road surface; the space occupancy rate of the target area is used to indicate the degree of restriction of the target robot's movement in the target area.

[0105] The control parameter of the robot is switched from a third parameter value to a fourth parameter value; the third parameter value is a parameter value corresponding to the third category, and the fourth parameter value is a parameter value corresponding to the fourth category.

[0106] See also Figure 3 , Figure 3 This is a schematic block diagram of a robot controller provided by an embodiment of the present disclosure. Figure 3The robot controller 300 in the embodiment shown may include: one or more processors 301, one or more input devices 302, one or more output devices 303, and one or more memories 304. The processors 301, input devices 302, output devices 303, and memories 304 communicate with each other via a communication bus 305. The memory 304 is used to store computer programs, which include program instructions. The processor 301 is used to execute the program instructions stored in the memory 304. The processor 301 is configured to call the program instructions to execute the functions of the modules / units in the above-mentioned device embodiments, such as Figure 2 The functions of modules 21 to 24 are shown.

[0107] It should be understood that in the embodiments of the present disclosure, the processor 301 may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0108] The input device 302 may include a touchpad, a fingerprint sensor (for collecting the user's fingerprint information and fingerprint direction information), a microphone, etc. The output device 303 may include a display (LCD, etc.), a speaker, etc.

[0109] The memory 304 may include a read-only memory and a random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include a non-volatile random access memory. For example, the memory 304 may also store device type information.

[0110] In a specific implementation, the processor 301, input device 302, and output device 303 described in the embodiments of the present disclosure can execute the implementation methods described in the first and second embodiments of a robot control method for automatic operation under complex road conditions provided by the embodiments of the present disclosure, and can also execute the implementation methods of the robot controller described in the embodiments of the present disclosure, which will not be repeated here.

[0111] In another embodiment of the present disclosure, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program. The computer program includes program instructions. When the program instructions are executed by a processor, all or part of the process of the method in the above embodiment is implemented. The computer program can also be used to instruct related hardware to complete the process. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of each of the above method embodiments are implemented. The computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium.

[0112] The computer-readable storage medium can be the internal storage unit of the robot controller in any of the aforementioned embodiments, such as the robot controller's hard drive or memory. The computer-readable storage medium can also be an external storage device of the robot controller, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Furthermore, the computer-readable storage medium can include both the robot controller's internal storage unit and an external storage device. The computer-readable storage medium is used to store computer programs and other programs and data required by the robot controller. The computer-readable storage medium can also be used to temporarily store data that has been output or is about to be output.

[0113] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the composition and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this disclosure.

[0114] Those skilled in the art will clearly understand that, for the sake of convenience and brevity of description, the specific working processes of the robot controller and unit described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0115] In the several embodiments provided in this application, it should be understood that the disclosed robot controller and method can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is merely a logical functional division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface or unit, or can be an electrical, mechanical or other form of connection.

[0116] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of these units may be selected based on actual needs to achieve the objectives of the embodiments of the present disclosure.

[0117] In addition, the functional units in the various embodiments of the present disclosure may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0118] The above are only specific embodiments of the present disclosure, but the scope of protection of the present disclosure is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or replacements within the technical scope disclosed in this disclosure, and such modifications or replacements should be included in the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure should be based on the scope of protection of the claims.

Claims

1. A robot control method for automatic operation in complex road conditions, characterized in that: include: Determining road condition classification information of the target area based on environmental perception information of the target area; The target area is the current operating area of the target robot; determining a category of a target area based on the road condition classification information; In response to the category of the target area changing from the first category to the second category, switching a control parameter of the robot from a first parameter value to a second parameter value; The first parameter value is a parameter value corresponding to the first category, and the second parameter value is a parameter value corresponding to the second category; Performing operation control of the target robot based on the control parameters; Also includes: In response to the category of the target area being the third category, calculating an average running speed of the target robot within the first time period; In response to an average running speed of the target robot being less than a first speed threshold, calculating a space occupancy rate of the target area based on environmental perception information of the target area; In response to the spatial occupancy rate of the target area being greater than a first threshold, switching the category of the target area to a fourth category; switching the control parameter of the robot from a third parameter value to a fourth parameter value; the third parameter value being a parameter value corresponding to the third category, and the fourth parameter value being a parameter value corresponding to the fourth category; The third category is used to indicate that the road surface of the target area is a flat road surface, and the fourth category is used to indicate that the road surface of the target area is a narrow road surface; the space occupancy rate of the target area is used to indicate the degree of restriction of the target robot's movement in the target area.

2. A robot control method for automatic operation in complex road conditions according to claim 1, characterized in that: Switching the control parameter of the robot from the first parameter value to the second parameter value includes: In response to the control parameter belonging to a first type of control parameter, switching the control parameter from a first parameter value to a second parameter value; the first type of control parameter is a control parameter other than a motor operation control parameter; In response to the control parameter belonging to the second type of control parameter, the first parameter value is converted into multiple third parameter values in sequence with a first step length, and the multiple third parameter values are determined as the control parameter in sequence; the second type of control parameter is the control parameter of the motor operation.

3. A robot control method for automatic operation in complex road conditions according to claim 1, characterized in that: The determining of the road condition classification information of the target area based on the environmental perception information of the target area includes: Performing image recognition on the image of the target area to obtain an image recognition result; Determine the traffic classification information of the target area based on the image recognition result.

4. A robot control method for automatic operation in complex road conditions according to claim 1, characterized in that: Also includes: In response to a pedestrian flow in the target area being greater than a flow threshold, a control parameter of the target robot is adjusted based on the pedestrian flow.

5. The method for controlling a robot that automatically operates in complex road conditions according to claim 1, characterized in that: Also includes: In response to the category of the target area being the fourth category and the height of the obstacle being less than the height threshold, the obstacle avoidance mode of the target robot is set to the first obstacle avoidance mode, and in the first obstacle avoidance mode, the target robot is controlled to cross the obstacle.

6. The method for controlling a robot that automatically operates in complex road conditions according to claim 1, characterized in that: Also includes: In response to the category of the target area being the fourth category, calculating an average running speed of the target robot within the first time period; In response to an average operating speed of the target robot being greater than a second speed threshold, calculating a space occupancy rate of the target area based on environmental perception information of the target area; In response to the spatial occupancy rate of the target area being less than a second threshold, switching the category of the target area to a third category; the third category is used to indicate that the road surface of the target area is a flat road surface, and the fourth category is used to indicate that the road surface of the target area is a narrow road surface; the spatial occupancy rate of the target area is used to indicate the degree of restriction of the target robot's movement in the target area; Switching the control parameter of the robot from the third parameter value to the fourth parameter value; The third parameter value is a parameter value corresponding to the third category, and the fourth parameter value is a parameter value corresponding to the fourth category.

7. A robot control device that automatically operates in complex road conditions, characterized in that: A device capable of realizing the content of the robot control method for automatic operation in complex road conditions as described in any one of claims 1 to 6; the device comprises: A first classification module is configured to determine road condition classification information of a target area based on environmental perception information of the target area; the target area is a current operating area of the target robot; a second classification module, configured to determine a category of a target area based on the road condition classification information; a parameter switching module, configured to switch a control parameter of the robot from a first parameter value to a second parameter value in response to a change in the category of the target area from the first category to the second category; The first parameter value is a parameter value corresponding to the first category, and the second parameter value is a parameter value corresponding to the second category; A control output module, configured to control the operation of the target robot based on the control parameters; The second classification module is specifically used for: In response to the category of the target area being the third category, calculating an average running speed of the target robot within the first time period; In response to an average operating speed of the target robot being less than a first speed threshold, calculating a spatial occupancy rate of the target area based on environmental perception information of the target area; In response to the spatial occupancy rate of the target area being greater than the first threshold, switching the category of the target area to a fourth category; switching the control parameter of the robot from a third parameter value to a fourth parameter value; the third parameter value being a parameter value corresponding to the third category, and the fourth parameter value being a parameter value corresponding to the fourth category; The third category is used to indicate that the road surface of the target area is flat, and the fourth category is used to indicate that the road surface of the target area is narrow; the space occupancy rate of the target area is used to indicate the degree of restriction of the target robot's movement in the target area.

8. A robot controller comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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