Anti-slip movement control method for AMR robot and AMR robot

Abstract

The invention relates to the technical field of AMR robots, and provides an AMR robot-oriented anti-slip movement control method and an AMR robot, and the method comprises the steps: determining a target wheel with a slip trend based on the real-time driving torque, collected by a driving motor of the AMR robot, of each wheel; based on the four-quadrant self-adaptive impedance, the current driving torque of the target wheel and the wheel torque difference value between the adjacent wheels are combined, and self-adaptive impedance adjusting parameters of the target wheel are determined; corresponding impedance control is applied to a driving motor of the target wheel based on the self-adaptive impedance adjustment parameter of the target wheel, and the adjusted output torque of the target wheel is obtained; and the moving posture and the moving speed of the AMR robot are adjusted based on the adjusted output torque till the AMR robot does not have the slipping trend. The operation stability of the AMR robot in the operation process is improved.

Description

Technical Field

[0001] This invention relates to the field of AMR robot technology, and in particular to an anti-slip movement control method for AMR robots and an AMR robot. Background Technology

[0002] With the rapid development of intelligent manufacturing and logistics automation, autonomous mobile robots (AMRs) have been widely used in industrial production, warehousing and logistics. AMRs, through autonomous path planning and movement, can efficiently complete tasks such as material handling and equipment inspection, greatly improving production efficiency and logistics management. However, in complex and changing operating environments, ground conditions are often unpredictable, such as the presence of oil stains, water stains, dust, uneven ground materials, or slopes. These factors can cause AMRs to slip during movement. Slippage not only reduces the positioning accuracy of the AMR, preventing it from accurately following the predetermined path, but may also lead to collisions, damaging the robot itself and surrounding equipment, seriously affecting the continuity and safety of production operations.

[0003] To address the slippage problem in AMR robots, existing anti-slip movement control methods primarily rely on monitoring wheel speed to determine if slippage has occurred and adjusting the wheel speed when slippage is detected. However, depending solely on wheel speed as a single parameter for judgment and control cannot comprehensively consider the force conditions experienced by the robot under different working conditions. This results in poor control performance in complex environments, failing to effectively suppress slippage and affecting the operational stability of the AMR robot during operation. Summary of the Invention

[0004] This invention provides an anti-slip movement control method for AMR robots and an AMR robot, in order to improve the operational stability of AMR robots during operation.

[0005] In a first aspect, the present invention provides an anti-slip movement control method for AMR robots, comprising:

[0006] Based on the real-time drive torque of each wheel collected by the drive motor of the AMR robot, the target wheel with a slippage tendency is identified.

[0007] The adaptive impedance adjustment parameters of the target wheel are determined based on the four-quadrant adaptive impedance combined with the current driving torque of the target wheel and the wheel torque difference between adjacent wheels.

[0008] Based on the adaptive impedance adjustment parameters of the target wheel, corresponding impedance control is applied to the drive motor of the target wheel to obtain the adjusted output torque of the target wheel;

[0009] adjust the moving posture and moving speed of the AMR robot based on the adjusted output torque until the AMR robot has no tendency of slipping.

[0010] In a second aspect, the present application further provides an AMR robot, which is applied to the anti-slip moving control method for the AMR robot as described in the first aspect; the AMR robot comprises:

[0011] a slip monitoring module, configured to determine a target wheel having a tendency of slipping based on the real-time driving torque of each wheel collected by the driving motor of the AMR robot;

[0012] an impedance adjusting module, configured to determine an adaptive impedance adjusting parameter of the target wheel based on the four-quadrant adaptive impedance and the current driving torque of the target wheel and the wheel torque difference value between adjacent wheels;

[0013] an impedance control module, configured to apply corresponding impedance control to the driving motor of the target wheel based on the adaptive impedance adjusting parameter of the target wheel, so as to obtain an adjusted output torque of the target wheel;

[0014] a moving control module, configured to adjust the moving posture and moving speed of the AMR robot based on the adjusted output torque until the AMR robot has no tendency of slipping.

[0015] In a third aspect, the present application further provides an electronic device, comprising: a memory, configured to store a computer software program; and a processor, configured to read and execute the computer software program, so as to realize the anti-slip moving control method for the AMR robot as described above.

[0016] In a fourth aspect, the present application further provides a non-transitory computer readable storage medium, wherein the storage medium stores a computer software program, and the computer software program is executed by a processor to realize the anti-slip moving control method for the AMR robot as described above.

[0017] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, and the computer program is executed by a processor to realize the anti-slip moving control method for the AMR robot as described above.

[0018] The anti-slip movement control method for the AMR robot provided by the embodiment of the present application can quickly locate the target wheel with the slip trend based on the slip trend judgment result, and in combination with the four-quadrant adaptive impedance, the current driving torque of the target wheel and the torque difference value, deeply analyzes the stress characteristics of the target wheel, so that the determined adaptive impedance adjustment parameter has stronger working condition adaptability, the impedance control is applied to the target wheel driving motor according to the adaptive impedance adjustment parameter, the output torque of the target wheel can be more effectively adjusted, and it is more suitable for actual operation requirements, finally, the movement posture and movement speed of the robot are dynamically optimized by using the adjusted output torque, and the slip trend is eliminated, so that the stress conditions of the robot in different working conditions can be comprehensively considered, the slip phenomenon can be effectively inhibited, and the running stability of the AMR robot in the operation process is improved. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is a flowchart of the anti-slip movement control method for the AMR robot provided by the embodiment of the present application;

[0020] Figure 2 is a structural schematic diagram of the AMR robot provided by the embodiment of the present application;

[0021] Figure 3 is an embodiment diagram of an electronic device provided by the embodiment of the present application;

[0022] Figure 4 is an embodiment diagram of a computer readable storage medium provided by the embodiment of the present application. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0024] In the description of the present application, the terms "first", "second" are only used for description purpose, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "multiple" is two or more, unless otherwise specifically limited.

[0025] In the description of the present application, the term "for example" is used to indicate "serving as an example, instance, or illustration." Any embodiment described as "for example" in the present application is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to practice the present application as claimed. In the following description, details are set forth in order to provide a thorough understanding of the present application. It will be apparent to one ordinarily skilled in the art that the present application can be practiced without using these specific details. In other instances, well-known structures and processes have not been elaborated in order to avoid unnecessary detail, which might obscure the description of the present application. Therefore, the present application is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

[0026] Referring to Figure 1 , Figure 1 is a flowchart of the anti-slip moving control method for the AMR robot provided by the present application. The execution subject of the anti-slip moving control method for the AMR robot in the present embodiment is the AMR robot. Therefore, the anti-slip moving control method for the AMR robot includes:

[0027] Step 10, determining the target wheel with a tendency of slipping based on the real-time driving torque of each wheel collected by the driving motor of the AMR robot.

[0028] Optionally, the driving motor of the AMR robot collects the driving torque of the four wheels (left front wheel, right front wheel, left rear wheel, and right rear wheel) in real time, analyzes the vehicle lateral torque imbalance direction and the vehicle longitudinal torque imbalance direction according to the real-time driving torque of the four wheels, and identifies the target wheel with a tendency of slipping according to the vehicle lateral torque imbalance direction and the vehicle longitudinal torque imbalance direction. The specific process is as shown in steps 101 to 104. It should be noted that the target wheel in the present embodiment only exists in a single wheel case, i.e., the target wheel can be the left front wheel, the right front wheel, the left rear wheel, or the right rear wheel.

[0029] Step 20, determining the adaptive impedance adjustment parameter of the target wheel based on the four-quadrant adaptive impedance, the current driving torque of the target wheel, and the wheel torque difference value between adjacent wheels.

[0030] Further, the AMR robot calculates the adaptive impedance adjustment parameter (including the stiffness coefficient and the damping coefficient) of the target wheel based on the four-quadrant adaptive impedance control theory, the current driving torque of the target wheel, and the torque difference value between adjacent wheels. Specifically, the four quadrants correspond to different motion states (forward driving, forward braking, reverse driving, and reverse braking) of the wheels. The belonging quadrant needs to be determined according to the motion direction (forward / reverse) and the torque direction (driving / braking) of the target wheel, and then the impedance parameter is adjusted accordingly. The specific process is as shown in steps 201 to 216.

[0031] Step 30, based on the adaptive impedance adjustment parameters of the target wheel, the corresponding impedance control is applied to the drive motor of the target wheel, and the adjusted output torque of the target wheel is obtained.

[0032] Further, the control system of the AMR robot applies impedance control to the drive motor of the target wheel according to the adaptive impedance adjustment parameters (stiffness coefficient K, damping coefficient B).

[0033] The core of the impedance control in the embodiment of the application is to adjust the motor output torque, so that the deviation of the motion state (position, speed) of the target wheel from the preset trajectory meets the impedance relationship: , wherein Δx is the deviation of the actual position of the target wheel from the expected position, and Δv is the deviation of the actual speed from the expected speed. Finally, the adjusted torque calculated by the impedance control is superimposed with the original driving torque to obtain the adjusted output torque of the target wheel, so as to increase the friction between the wheel and the ground and suppress the slipping trend.

[0034] In an embodiment, the adaptive impedance adjustment parameters of the left front wheel of the target wheel are , The real-time detection shows that the actual position of the left front wheel lags behind the expected position by Δx=0.02m (due to insufficient position caused by slipping), and the actual speed is lower than the expected speed by According to the impedance control formula, the adjustment torque is The original driving torque is Therefore, the adjusted output torque is , which is output to the left front wheel drive motor through the motor controller.

[0035] Step 40, based on the adjusted output torque, the moving posture and moving speed of the AMR robot are adjusted until the AMR robot does not have a slipping trend.

[0036] Further, the AMR robot adjusts the overall moving posture and moving speed according to the adjusted output torque of the target wheel through the motion control system, which specifically includes:

[0037] If a single wheel (such as the left front wheel) is adjusted, in order to avoid the robot from deviating, a reverse compensation torque (adjusted according to the torque difference between the two sides in proportion) needs to be applied to the symmetric wheel on the other side (such as the right front wheel), so that the driving torques on both sides remain balanced and the driving direction is stable.

[0038] If the adjusted torque of the target wheel increases significantly, it indicates that the ground friction is insufficient, and the overall moving speed of the robot needs to be reduced (such as from 1m / s to 0.6m / s) to reduce the driving demand and avoid the slipping from being aggravated.

[0039] Collecting each wheel torque continuously and repeating steps 10-30 until all wheel torques return to normal interval and no slip tendency, stop adjusting.

[0040] Continuing the above example, the left front wheel adjusted output torque , the right front wheel original torque , the two sides torque difference is To adjust the posture, the right front wheel is applied with a compensation torque (compensation coefficient 0.5), the right front wheel adjusted torque is , ensuring the balance of the front wheel torque on both sides. At the same time, because the left front wheel torque is significantly improved, it is determined that the ground friction is low, and the overall movement speed of the robot is reduced from 1 m / s to 0.7 m / s. After continuously monitoring for 5 cycles, the left front wheel torque stabilizes at (return to normal interval), and other wheel torques are normal with no slip tendency, and the adjustment is stopped.

[0041] The embodiment of the present application quickly locates the target wheel with slip tendency based on the slip tendency judgment result, and combines the four-quadrant adaptive impedance, the current drive torque of the target wheel and the torque difference value to deeply analyze the force characteristics of the target wheel, so that the determined adaptive impedance adjustment parameter has stronger working condition adaptability. According to the adaptive impedance adjustment parameter, impedance control is applied to the drive motor of the target wheel, which can more effectively adjust the output torque of the target wheel to better meet the actual operation demand. Finally, the movement posture and movement speed of the robot are dynamically optimized by using the adjusted output torque to eliminate the slip tendency. Therefore, the force conditions of the robot in different working conditions can be comprehensively considered, and the running stability of the AMR robot in the operation process is improved.

[0042] In an embodiment, the process of steps 101 to 104 includes:

[0043] Step 101, determining a lateral front wheel torque difference value based on the difference between the real-time drive torque of the left front wheel and the real-time drive torque of the right front wheel, and determining a lateral rear wheel torque difference value based on the difference between the real-time drive torque of the left rear wheel and the real-time drive torque of the right rear wheel.

[0044] Step 102, determining a left longitudinal wheel torque difference value based on the difference between the real-time drive torque of the left front wheel and the real-time drive torque of the left rear wheel, and determining a right longitudinal wheel torque difference value based on the difference between the real-time drive torque of the right front wheel and the real-time drive torque of the right rear wheel.

[0045] Optionally, the AMR robot collects the driving torque of the four wheels (left front wheel, right front wheel, left rear wheel, right rear wheel) in real time, and then calculates the lateral and longitudinal torque difference values. The lateral torque difference value is used to reflect the torque difference between the left and right wheels of the same row (front wheel row, rear wheel row), and the longitudinal torque difference value is used to reflect the torque difference between the front and rear wheels of the same side (left side, right side). The left side longitudinal wheel torque difference value reflects the torque comparison relationship between the left front wheel and the left rear wheel, and the right side longitudinal wheel torque difference value reflects the torque comparison relationship between the right front wheel and the right rear wheel. Through the two difference values, it can be judged whether there is an abnormal difference in the torque of the front and rear wheels of the same side (usually when driving normally, the torque difference between the front and rear wheels of the same side should be within a preset range, such as ). The specific calculation method is: lateral front wheel torque difference value = left front wheel real-time driving torque - right front wheel real-time driving torque; lateral rear wheel torque difference value = left rear wheel real-time driving torque - right rear wheel real-time driving torque; left side longitudinal wheel torque difference value = left front wheel real-time driving torque - left rear wheel real-time driving torque; right side longitudinal wheel torque difference value = right front wheel real-time driving torque - right rear wheel real-time driving torque. The difference value can be positive, negative or zero, and a positive value indicates that the left side (or front wheel) torque is greater than the right side (or rear wheel), and a negative value indicates the opposite.

[0046] In an embodiment, the AMR robot drives on a dry cement floor, and the real-time collected driving torque of the four wheels is as follows: left front wheel , right front wheel , left rear wheel , and right rear wheel . Therefore, the lateral front wheel torque difference value = left front wheel real-time driving torque - right front wheel real-time driving torque = ; the lateral rear wheel torque difference value = left rear wheel real-time driving torque - right rear wheel real-time driving torque = ; the left side longitudinal wheel torque difference value = left front wheel real-time driving torque - left rear wheel real-time driving torque = (indicating that the left front wheel torque is lower than the left rear wheel ); and the right side longitudinal wheel torque difference value = right front wheel real-time driving torque - right rear wheel real-time driving torque = (indicating that the right front wheel torque is higher than the right rear wheel ). Assuming that the normal left side longitudinal torque difference range of the AMR robot when driving on a dry cement floor is , and the normal right side longitudinal torque difference range is also , at this time, the left side longitudinal difference value ( ) is out of the normal range, and the right side longitudinal difference value ( ) is within the normal range.

[0047] Step 103, determine the vehicle lateral torque imbalance direction based on the lateral front wheel torque difference value and the lateral rear wheel torque difference value, and determine the vehicle longitudinal torque imbalance direction based on the left side longitudinal wheel torque difference value and the right side longitudinal wheel torque difference value.

[0048] Further, the AMR robot determines the vehicle lateral torque imbalance direction based on the lateral front wheel torque difference value, the lateral rear wheel torque difference value, and determines the vehicle longitudinal torque imbalance direction based on the left side longitudinal wheel torque difference value and the right side longitudinal wheel torque difference value.

[0049] Wherein, the lateral torque imbalance direction judgment: if the lateral front wheel torque difference value and the lateral rear wheel torque difference value are both negative values, it means that the left side wheel (front wheel and rear wheel) torque is less than the right side corresponding wheel, and the lateral imbalance direction is "left side torque is low"; if they are both positive values, it means that the left side wheel torque is greater than the right side, and the lateral imbalance direction is "right side torque is low"; if the signs are opposite, the dominant imbalance direction needs to be judged in combination with the absolute value (such as when the front wheel difference value absolute value is larger, the lateral front wheel difference is dominant).

[0050] The longitudinal torque imbalance direction judgment: if the left side longitudinal wheel torque difference value is negative and exceeds the normal range, it means that the left side front wheel torque is less than the left side rear wheel, and the left side longitudinal imbalance direction is "left side front wheel torque is low"; if the right side longitudinal wheel torque difference value is negative and exceeds the normal range, it means that the right side front wheel torque is less than the right side rear wheel, and the right side longitudinal imbalance direction is "right side front wheel torque is low" (when the positive value exceeds the range, it is the rear wheel torque that is low).

[0051] In an embodiment, the lateral front wheel torque difference value = (negative value), the lateral rear wheel torque difference value = (negative value), and both exceed the normal lateral difference range ( ), so the vehicle lateral torque imbalance direction is "left side torque is low";

[0052] The left side longitudinal wheel torque difference value = (negative value, exceeding the normal range ), which means that the left side front wheel torque is significantly lower than the left side rear wheel, so the left side longitudinal torque imbalance direction is "left side front wheel torque is low"; the right side longitudinal difference value is within the normal range, and there is no right side longitudinal imbalance.

[0053] Step 104, determine the target wheel with a tendency to slip based on the vehicle lateral torque imbalance direction and the vehicle longitudinal torque imbalance direction.

[0054] Further, the AMR robot determines the target wheel with a tendency to slip according to the vehicle lateral torque imbalance direction and the vehicle longitudinal torque imbalance direction, specifically as the process of step 1041 to step 1045.

[0055] The embodiment of the present application can accurately identify the wheel with the tendency of slipping through multi-dimensional torque difference analysis, can exclude the misjudgment caused by the simultaneous influence of road conditions on single side or single row of wheels (such as single side ground mud), and improves the accuracy of identifying the target wheel with the tendency of slipping through cross verification of lateral and longitudinal imbalance, thereby improving the running stability of the AMR robot in the working process.

[0056] In an embodiment, the process of steps 1041 to 1045 includes:

[0057] Step 1041, superimposing the directions based on the vehicle lateral torque imbalance direction and the vehicle longitudinal torque imbalance direction to obtain a torque imbalance superposition direction.

[0058] Optionally, the AMR robot superimposes the directions based on the vehicle lateral torque imbalance direction and the vehicle longitudinal torque imbalance direction to obtain a torque imbalance superposition direction.

[0059] It should be noted that the lateral torque imbalance direction of the embodiment of the present application includes two cases of "left side torque low" and "right side torque low", and the longitudinal torque imbalance direction includes four cases of "left side front wheel torque low", "left side rear wheel torque low", "right side front wheel torque low" and "right side rear wheel torque low". The logic of direction superposition is: cross positioning of the lateral direction and the longitudinal direction - if the lateral imbalance is "left side torque low" and the longitudinal imbalance is "left side front wheel torque low", the superposition direction is "left front direction"; if the lateral imbalance is "right side torque low" and the longitudinal imbalance is "right side rear wheel torque low", the superposition direction is "right rear direction", and so on. Through the combination of the lateral and longitudinal directions, the position (left front, right front, left rear, right rear) of a wheel is uniquely determined.

[0060] In an embodiment, the vehicle lateral torque imbalance direction is "left side torque low", and the vehicle longitudinal torque imbalance direction is "left side front wheel torque low". Superimposing the two directions: the cross position of the lateral "left side" and the longitudinal "left front" is the left front direction, so the torque imbalance superposition direction is the left front direction.

[0061] Step 1042, if the torque imbalance superposition direction is the left front direction, the target wheel is determined as the left front wheel.

[0062] Further, when the torque imbalance superposition direction is the left front direction, the AMR robot determines that the target wheel with the tendency of slipping is the left front wheel, because the left front direction is the only orientation of the left front wheel, and the superposition result of the lateral and longitudinal torque imbalances points to this wheel, indicating that its torque is abnormally low and is the core reason for the overall torque imbalance, which meets the characteristics of the tendency of slipping (the torque is significantly lower than the normal range and is significantly different from other wheels). Continuing the above embodiment, step 1041 obtains that the torque imbalance superposition direction is the left front direction, and therefore the AMR robot determines that the target wheel is the left front wheel.

[0063] Step 1043, if the torque imbalance superposition direction is the right front direction, the target wheel is determined to be the right front wheel.

[0064] Further, when the torque imbalance superposition direction is the right front direction, the AMR robot determines that the target wheel with the tendency of slipping is the right front wheel. The right front direction corresponds to the orientation of the right front wheel, and the superposition result of the lateral and longitudinal torque imbalances points to this wheel, indicating that its torque is abnormally low and is the main source of torque imbalance, which meets the determination condition of the tendency of slipping. Assuming another scenario, the vehicle lateral torque imbalance direction is “right side torque is low”, and the longitudinal torque imbalance direction is “right side front wheel torque is low”, step 1041 obtains that the torque imbalance superposition direction is the right front direction, and therefore the AMR robot determines that the target wheel is the right front wheel.

[0065] Step 1044, if the torque imbalance superposition direction is the left rear direction, the target wheel is determined to be the left rear wheel.

[0066] Further, when the torque imbalance superposition direction is the left rear direction, the AMR robot determines that the target wheel with the tendency of slipping is the left rear wheel. The left rear direction is the only orientation of the left rear wheel, and the superposition result of the lateral and longitudinal torque imbalances points to this wheel, indicating that its torque is abnormally low and is the key to the overall torque imbalance, which meets the characteristics of the tendency of slipping. Assuming another scenario, the vehicle lateral torque imbalance direction is “left side torque is low”, and the longitudinal torque imbalance direction is “left side rear wheel torque is low”, step 1041 obtains that the torque imbalance superposition direction is the left rear direction, and therefore the AMR robot determines that the target wheel is the left rear wheel.

[0067] Step 1045, if the torque imbalance superposition direction is the right rear direction, the target wheel is determined to be the right rear wheel.

[0068] Further, when the torque imbalance superposition direction is the right rear direction, the AMR robot determines that the target wheel with the skid tendency is the right rear wheel. The right rear direction corresponds to the orientation of the right rear wheel, and the superposition result of the lateral and longitudinal torque imbalances points to the wheel, indicating that the abnormally low torque of the wheel is the main cause of the torque imbalance, which meets the determination condition of the skid tendency. Assuming another scenario, the vehicle lateral torque imbalance direction is "low right torque", and the longitudinal torque imbalance direction is "low right rear wheel torque", and step 1041 obtains the torque imbalance superposition direction as the right rear direction, and the AMR robot determines that the target wheel is the right rear wheel.

[0069] The embodiment of the application converts two-dimensional (lateral and longitudinal) torque imbalance information into the positioning of a specific wheel through the logic of direction superposition, improves the accuracy of identifying the target wheel with the skid tendency, and improves the running stability of the AMR robot in the working process.

[0070] In an embodiment, the process of steps 201 to 204 includes:

[0071] Step 201: If the target wheel is the left front wheel, determine the torque action direction of the left front wheel based on the current driving torque of the left front wheel, and determine the torque advantage direction of the left front wheel relative to the right front wheel based on the lateral front wheel torque difference value between the left front wheel and the right front wheel.

[0072] Optionally, when the target wheel is the left front wheel, the AMR robot needs to determine the torque action direction of the left front wheel and the torque advantage direction relative to the right front wheel. For the torque action direction: according to the motion state (forward or backward) of the left front wheel and the output torque direction of the driving motor, the torque action direction is "forward driving direction" when driving forward, and "backward driving direction" when driving backward (normal driving is forward driving, and the torque action direction is the forward driving direction). For the torque advantage direction: based on the lateral front wheel torque difference value (left front wheel torque - right front wheel torque) between the left front wheel and the right front wheel, if the difference value is positive, it means that the left front wheel torque is greater than the right front wheel, and the advantage direction is "left front wheel torque dominant"; if the difference value is negative, it means that the left front wheel torque is less than the right front wheel, and the advantage direction is "right front wheel torque dominant"; if the difference value is zero, there is no advantage direction.

[0073] In an embodiment, the target wheel is the left front wheel, the current driving torque of the left front wheel is , and the AMR robot is in a forward driving state, so the torque action direction of the left front wheel is "forward driving direction". The lateral front wheel torque difference value is (left front wheel torque - right front wheel torque = 5 - 10), and the difference value is negative, so the torque advantage direction of the left front wheel relative to the right front wheel is "right front wheel torque dominant".

[0074] Step 202, based on the torque action direction and the torque advantage direction, determine the torque action quadrant of the left front wheel in the four-quadrant adaptive impedance.

[0075] Further, the AMR robot determines the torque action quadrant of the left front wheel based on the torque action direction and the torque advantage direction of the left front wheel, and the division rule of the four-quadrant adaptive impedance.

[0076] In the embodiment of the present application, the four-quadrant division takes the "torque action direction" as the vertical axis (forward driving is positive direction, and backward driving is negative direction), and the "torque difference value sign corresponding to the torque advantage direction" as the horizontal axis (left front wheel torque dominant is positive direction, and right front wheel torque dominant is negative direction):

[0077] The first quadrant: the torque action direction is the forward driving direction, and the torque advantage direction is the right front wheel torque dominant (the difference value is negative); the second quadrant: the torque action direction is the backward driving direction, and the torque advantage direction is the right front wheel torque dominant (the difference value is negative); the third quadrant: the torque action direction is the backward driving direction, and the torque advantage direction is the left front wheel torque dominant (the difference value is positive); the fourth quadrant: the torque action direction is the forward driving direction, and the torque advantage direction is the left front wheel torque dominant (the difference value is positive).

[0078] Continuing the above embodiment, the torque action direction of the left front wheel is "forward driving direction" (vertical axis positive direction), and the torque advantage direction is "right front wheel torque dominant" (horizontal axis negative direction), which meets the characteristics of the first quadrant in the four-quadrant, so the torque action quadrant of the left front wheel in the four-quadrant adaptive impedance is the first quadrant.

[0079] Step 203, based on the left side longitudinal wheel torque difference value between the left front wheel and the left rear wheel, determine the torque difference degree of the left front wheel relative to the left rear wheel.

[0080] Further, the AMR robot determines the torque difference degree of the left front wheel relative to the left rear wheel based on the left side longitudinal wheel torque difference value (left front wheel torque-left rear wheel torque) between the left front wheel and the left rear wheel. The difference degree is determined by comparing the absolute value of the difference value with the preset longitudinal torque difference threshold: if the absolute value is less than or equal to the threshold, it is "slight difference"; if the absolute value is greater than the threshold and less than or equal to twice the threshold, it is "moderate difference"; if the absolute value is greater than twice the threshold, it is "significant difference". The difference degree reflects the torque imbalance severity of the left front wheel and the same side rear wheel, and is an important basis for adjusting the impedance parameters.

[0081] Continuing the above embodiment, the left side longitudinal wheel torque difference value is (left front wheel torque-left rear wheel torque=5-8), and the absolute value is . Assuming that the preset longitudinal torque difference threshold is Greater than 2 times the threshold value, so the torque difference degree of the left front wheel relative to the left rear wheel is "significant difference".

[0082] Step 204, based on the diagonal wheel torque difference value between the left front wheel and the right rear wheel, the impedance adjustment parameter of the left front wheel is determined by combining the torque difference degree and the impedance adjustment reference corresponding to the torque action quadrant.

[0083] Further, the AMR robot calculates the diagonal wheel torque difference value (left front wheel torque-right rear wheel torque) of the left front wheel and the right rear wheel, and then determines the adaptive impedance adjustment parameter (stiffness coefficient, damping coefficient) of the left front wheel by combining the torque difference degree and the impedance adjustment reference (different quadrant preset different stiffness coefficient reference value and damping coefficient reference value) corresponding to the torque action quadrant. The specific logic is: the greater the absolute value of the diagonal torque difference value, the more significant the torque difference degree, and the greater the increase amplitude of the impedance adjustment parameter (stiffness, damping) relative to the reference value (because the target wheel torque is low, the impedance needs to be enhanced to suppress slipping).

[0084] Continuing the above embodiment, the current drive torque of the left front wheel is , the right rear wheel torque is , so the diagonal wheel torque difference value is , and the absolute value is . Step 202 determines that the torque action quadrant is the first quadrant, and its impedance adjustment reference is: stiffness coefficient reference value , damping coefficient reference value . Step 203 determines that the torque difference degree is "significant difference", and the corresponding adjustment coefficient is: stiffness increase coefficient , damping increase coefficient (the more significant the difference, the greater the coefficient). Then the adaptive impedance adjustment parameter is:

[0085] Stiffness coefficient K=K0+diagonal torque difference value absolute value ;

[0086] Damping coefficient B=B0+diagonal torque difference value absolute value .

[0087] The embodiment of the application realizes precise impedance parameter configuration for the slipping trend of the left front wheel by multi-dimensional torque difference (lateral, longitudinal, diagonal) and four-quadrant impedance rules, ensures that the adjustment parameter can match the motion state of the target wheel, and dynamically optimizes according to the torque imbalance degree, thereby improving the pertinence of slipping suppression.

[0088] In an embodiment, the process of steps 205 to 208 includes:

[0089] Step 205, if the target wheel is the right front wheel, then the torque peak feature of the right front wheel is obtained based on the current driving torque of the right front wheel, and the torque peak difference feature of the right front wheel relative to the right rear wheel is obtained based on the right side longitudinal wheel torque difference value between the right front wheel and the right rear wheel.

[0090] Optionally, when the target wheel is the right front wheel, the AMR robot needs to obtain the torque peak feature of the right front wheel and the torque peak difference feature relative to the right rear wheel. The torque peak feature refers to the comparison relationship between the current driving torque of the right front wheel and the torque peak value of the wheel in this period (such as the maximum torque value in the past 10 sampling periods), including three cases of "current torque is lower than the peak value", "current torque is close to the peak value (the difference is within 10% of the peak value)", "current torque is equal to the peak value", reflecting the relative strength of the current torque of the right front wheel. The torque peak difference feature is calculated based on the right side longitudinal wheel torque difference value between the right front wheel and the right rear wheel, combined with the torque peaks of the two, that is, (right front wheel current torque - right front wheel peak) - (right rear wheel current torque - right rear wheel peak). If the result is negative, it means that the deviation of the current torque of the right front wheel relative to its peak value is greater than that of the right rear wheel, and the feature is "the deviation of the right front wheel peak value is more significant". If it is positive, it is the opposite. If it is zero, it means that the deviation is consistent.

[0091] In an embodiment, the right front wheel is the target wheel, its current driving torque is , the torque peak value in the past 10 periods is ("current torque is lower than the peak value"); the current torque of the right rear wheel is , the torque peak value in the past 10 periods is , and the right side longitudinal wheel torque difference value is .

[0092] The torque peak feature of the right front wheel is "current torque is lower than the peak value" ).

[0093] Torque peak difference feature calculation: , the result is negative, so the feature is "the deviation of the right front wheel peak value is more significant".

[0094] Step 206, based on the torque peak feature and the torque peak difference feature, determine the peak feature quadrant of the right front wheel in the four-quadrant adaptive impedance.

[0095] Further, the AMR robot determines the peak feature quadrant of the right front wheel based on the right front wheel torque peak feature and the torque peak difference feature, and the peak feature division rule of the four-quadrant adaptive impedance. The four-quadrant division takes the “torque peak feature” as the vertical axis (the current torque being lower than the peak value is negative, and close to or equal to the peak value is positive), and the “torque peak difference feature” as the horizontal axis (the right rear wheel peak value deviating more significantly is negative, and the right front wheel peak value deviating more significantly is positive). The first quadrant: the current torque is close to / equal to the peak value (vertical axis positive), and the right rear wheel peak value deviates more significantly (horizontal axis positive); the second quadrant: the current torque is close to / equal to the peak value (vertical axis positive), and the right front wheel peak value deviates more significantly (horizontal axis negative); the third quadrant: the current torque is lower than the peak value (vertical axis negative), and the right front wheel peak value deviates more significantly (horizontal axis negative); and the fourth quadrant: the current torque is lower than the peak value (vertical axis negative), and the right rear wheel peak value deviates more significantly (horizontal axis positive).

[0096] Continuing the above embodiment, the right front wheel torque peak feature is “the current torque is lower than the peak value” (vertical axis negative direction), and the torque peak difference feature is “the right front wheel peak value deviates more significantly” (horizontal axis negative direction), which meets the third quadrant feature, and the peak feature quadrant of the right front wheel in the four-quadrant adaptive impedance is the third quadrant.

[0097] Step 207, based on the lateral front wheel torque difference value between the right front wheel and the left front wheel, determine the torque transmission efficiency difference of the right front wheel relative to the left front wheel.

[0098] Further, the AMR robot determines the torque transmission efficiency difference of the right front wheel relative to the left front wheel based on the lateral front wheel torque difference value (right front wheel torque-left front wheel torque) between the right front wheel and the left front wheel, and the rated torque of the drive motor of both. The torque transmission efficiency difference is calculated by “(right front wheel current torque / right front wheel rated torque)-(left front wheel current torque / left front wheel rated torque)”, and the result is positive, indicating that the right front wheel transmission efficiency is higher than the left front wheel, the difference is “right front wheel efficiency dominant”; the result is negative, indicating that the right front wheel efficiency is lower than the left front wheel, the difference is “left front wheel efficiency dominant”; and the result is zero, indicating that the efficiency is consistent. The difference reflects the relative effectiveness of the power transmission of the two front wheels.

[0099] Continuing the above embodiment, the lateral front wheel torque difference value (right front wheel-left front wheel) is (assuming the left front wheel current torque , the right front wheel current torque , and the other wheel data in the previous scenario). The right front wheel rated torque is , and the left front wheel rated torque is .

[0100] The right front wheel transmission efficiency = 10 / 15 ≈ 66.7%; the left front wheel transmission efficiency = 5 / 15 ≈ 33.3%;

[0101] Efficiency difference = 66.7% - 33.3% = 33.4% > 0, so the torque transmission efficiency difference of the right front wheel relative to the left front wheel is "right front wheel efficiency dominant".

[0102] Step 208, based on the diagonal wheel torque difference value between the right front wheel and the left rear wheel, the impedance adjustment strategy of the torque transmission efficiency difference and the peak characteristic quadrant, determine the adaptive impedance adjustment parameter of the right front wheel.

[0103] Further, the AMR robot calculates the diagonal wheel torque difference value (right front wheel torque - left rear wheel torque) of the right front wheel and the left rear wheel, and then combines the torque transmission efficiency difference and the impedance adjustment strategy corresponding to the peak characteristic quadrant (different quadrants have different stiffness, damping adjustment direction and reference coefficient), to determine the adaptive impedance adjustment parameter (stiffness coefficient, damping coefficient) of the right front wheel. The specific logic is: the greater the absolute value of the diagonal torque difference value, the more significant the right front wheel efficiency dominant, and if the peak characteristic quadrant is a quadrant that needs to enhance the impedance (such as the third quadrant), the greater the increase of the impedance parameter relative to the reference value (to suppress the slipping trend).

[0104] Continue with the above embodiment, the current torque of the right front wheel , the torque of the left rear wheel , the diagonal wheel torque difference value is , and the absolute value is 2 . The peak characteristic quadrant is the third quadrant, and the impedance adjustment strategy is: the stiffness reference value , the damping reference value , and the efficiency dominant increase coefficient. Step 207 determines that the efficiency difference is "right front wheel efficiency dominant", and the corresponding adjustment coefficient is: stiffness increase coefficient k1 = 0.6, and damping increase coefficient k2 = 0.3. Then the adaptive impedance adjustment parameter is:

[0105] Stiffness coefficient K = K0 + absolute value of diagonal torque difference value ;

[0106] Damping coefficient B = B0 + absolute value of diagonal torque difference value .

[0107] The embodiment of the application combines the peak characteristic, the efficiency difference and the four-quadrant strategy to realize precise parameter configuration for the right front wheel slipping trend, so that the impedance parameter can match the torque dynamic characteristics of the right front wheel, and can adapt to the torque imbalance state in the horizontal and diagonal directions, improve the accuracy of slip suppression, and improve the running stability of the AMR robot in the working process.

[0108] In an embodiment, the process of steps 209 to 212 includes:

[0109] Step 209, if the target wheel is the left rear wheel, then based on the current driving torque of the left rear wheel, the torque variation period of the left rear wheel is extracted, and based on the left side longitudinal wheel torque difference value between the left rear wheel and the left front wheel, the torque variation period difference of the left rear wheel relative to the left front wheel is extracted.

[0110] Optionally, when the target wheel is the left rear wheel, the AMR robot needs to extract the torque variation period of the left rear wheel and the torque variation period difference relative to the left front wheel. The torque variation period refers to the period of the fluctuation of the driving torque of the left rear wheel with time. By analyzing the torque data of a plurality of continuous sampling periods (such as 20 periods, each period being 50 ms), the time interval from one peak to the next peak (or from one valley to the next valley) of the torque is identified, which is in seconds (s) and reflects the regularity of the torque fluctuation. For the torque variation period difference: based on the left side longitudinal wheel torque difference value between the left rear wheel and the left front wheel, the torque variation periods of the two are combined to calculate, i.e., the torque variation period of the left rear wheel minus the torque variation period of the left front wheel. If the result is positive, it means that the period of the left rear wheel is longer than that of the left front wheel, and the difference is “the period of the left rear wheel is longer”; if the result is negative, it means that the period of the left rear wheel is shorter than that of the left front wheel, and the difference is “the period of the left rear wheel is shorter”; if the result is zero, it means that the periods are consistent.

[0111] In an embodiment, the left rear wheel is the target wheel, and the fluctuation period of the continuous torque data thereof is analyzed to be 0.5 s (torque variation period); the torque variation period of the left front wheel is analyzed to be 0.3 s. The left side longitudinal wheel torque difference value is (left front wheel , left rear wheel ).

[0112] The torque variation period of the left rear wheel is 0.5 s;

[0113] The torque variation period difference is , so the feature is “the period of the left rear wheel is longer”.

[0114] Step 210, based on the torque variation period and the torque variation period difference, the period feature quadrant of the left rear wheel in the four-quadrant adaptive impedance is determined.

[0115] Further, the AMR robot determines the period characteristic quadrant of the left rear wheel based on the left rear wheel torque change period and the torque change period difference, combined with the period characteristic quadrant division rule of the four-quadrant adaptive impedance. The four-quadrant division takes the “torque change period” as the vertical axis (the period longer than the preset reference period is the positive direction, and the period shorter than the reference period is the negative direction, and the reference period is set based on the average period during normal driving, such as 0.4s), and the “torque change period difference” as the horizontal axis (the left rear wheel period longer is the positive direction, and the left rear wheel period shorter is the negative direction): the first quadrant: the torque change period is longer than the reference period (vertical axis positive), and the left rear wheel period is longer (horizontal axis positive); the second quadrant: the torque change period is longer than the reference period (vertical axis positive), and the left rear wheel period is shorter (horizontal axis negative); the third quadrant: the torque change period is shorter than the reference period (vertical axis negative), and the left rear wheel period is shorter (horizontal axis negative); and the fourth quadrant: the torque change period is shorter than the reference period (vertical axis negative), and the left rear wheel period is longer (horizontal axis positive).

[0116] Continuing the above embodiment, the preset reference period is 0.4s, the left rear wheel torque change period is 0.5s (longer than the reference period, vertical axis positive direction), and the torque change period difference is “left rear wheel period longer” (horizontal axis positive direction), which meets the characteristics of the first quadrant, so the period characteristic quadrant of the left rear wheel in the four-quadrant adaptive impedance is the first quadrant.

[0117] Step 211, determine the torque response sensitivity difference of the left rear wheel relative to the right rear wheel based on the lateral rear wheel torque difference value between the left rear wheel and the right rear wheel.

[0118] Further, the AMR robot determines the torque response sensitivity difference of the left rear wheel relative to the right rear wheel based on the lateral rear wheel torque difference value (left rear wheel torque-right rear wheel torque) between the left rear wheel and the right rear wheel, combined with the response time (from the issuance of the torque instruction to the torque change) of both to the torque instruction. The response sensitivity difference reflects the speed of the two rear wheels in responding to the driving instruction, and is calculated by “(1 / left rear wheel response time)-(1 / right rear wheel response time)” (the sensitivity is inversely proportional to the response time). If the result is positive, it means that the left rear wheel has higher sensitivity than the right rear wheel, and the difference is “left rear wheel sensitivity dominant”; if the result is negative, it means that the left rear wheel has lower sensitivity than the right rear wheel, and the difference is “right rear wheel sensitivity dominant”; and if the result is zero, it means that the sensitivity is consistent.

[0119] Continuing the above embodiment, the lateral rear wheel torque difference value (left rear wheel-right rear wheel) is (left rear wheel , right rear wheel ). The left rear wheel response time is 0.02s, and the right rear wheel response time is 0.01s.

[0120] Left rear wheel sensitivity = ; right rear wheel sensitivity = ;

[0121] Sensitivity difference , so the torque response sensitivity difference between the left rear wheel and the right rear wheel is "right rear wheel sensitivity dominant".

[0122] Step 212, based on the diagonal wheel torque difference value between the left rear wheel and the right front wheel, the torque response sensitivity difference and the impedance adjustment strategy corresponding to the periodic characteristic quadrant, the adaptive impedance adjustment parameter of the left rear wheel is determined.

[0123] Further, the AMR robot calculates the diagonal wheel torque difference value (left rear wheel torque-right front wheel torque) of the left rear wheel and the right front wheel, combines the torque response sensitivity difference and the impedance adjustment strategy corresponding to the periodic characteristic quadrant (different quadrants have different stiffness, damping adjustment reference and correction coefficient), and determines the adaptive impedance adjustment parameter (stiffness coefficient, damping coefficient) of the left rear wheel. The specific logic is: the greater the absolute value of the diagonal torque difference value, the more significant the right rear wheel sensitivity dominant, and if the periodic characteristic quadrant is a quadrant that needs to enhance the impedance (such as the first quadrant), the greater the increase of the impedance parameter relative to the reference value (to suppress the slipping trend).

[0124] Continuing the above embodiment, the current torque of the left rear wheel , the torque of the right front wheel , the diagonal wheel torque difference value , and the absolute value is . Step 210 determines that the periodic characteristic quadrant is the first quadrant, and the impedance adjustment strategy is: the stiffness reference value , the damping reference value , and the increase coefficient is improved when the sensitivity is poor. It is determined that the sensitivity difference is "right rear wheel sensitivity dominant" (left rear wheel sensitivity poor), and the corresponding adjustment coefficient is: stiffness increase coefficient k1=0.7, and damping increase coefficient k2=0.3. Then the adaptive impedance adjustment parameter is:

[0125] Stiffness coefficient K=K0+diagonal torque difference value absolute value ;

[0126] Damping coefficient B=B0+diagonal torque difference value absolute value .

[0127] The embodiment of the application combines the periodic characteristics, sensitivity difference and four-quadrant strategy to realize precise parameter configuration for the slipping trend of the left rear wheel, so that the impedance parameter can match the torque fluctuation law of the left rear wheel, and adapt to the torque imbalance state of the horizontal and diagonal directions, improve the stability of the slipping suppression, and improve the running stability of the AMR robot in the working process.

[0128] In an embodiment, the process of steps 213 to 216 includes:

[0129] Step 213, if the target wheel is the right rear wheel, then based on the current driving torque of the right rear wheel, the torque fluctuation frequency of the right rear wheel is identified, and based on the right side longitudinal wheel torque difference value between the right rear wheel and the right front wheel, the torque fluctuation frequency difference of the right rear wheel relative to the right front wheel is identified.

[0130] Optionally, when the target wheel is the right rear wheel, the AMR robot needs to identify the torque fluctuation frequency of the right rear wheel and the torque fluctuation frequency difference relative to the right front wheel. The torque fluctuation frequency refers to the number of fluctuations of the driving torque of the right rear wheel per unit time, which is extracted by performing frequency spectrum analysis (such as fast Fourier transform) on the torque data of a plurality of consecutive sampling periods (such as 30 periods, each period being 50 ms), and the frequency of the main fluctuation component is extracted, which is in hertz (Hz) and reflects the speed of torque fluctuation. For the torque fluctuation frequency difference, based on the right side longitudinal wheel torque difference value between the right rear wheel and the right front wheel, the torque fluctuation frequencies of the two are combined, that is, the torque fluctuation frequency of the right rear wheel minus the torque fluctuation frequency of the right front wheel. If the result is positive, it means that the frequency of the right rear wheel is higher than that of the right front wheel, and the difference is “the frequency of the right rear wheel is higher”; if the result is negative, it means that the frequency of the right rear wheel is lower than that of the right front wheel, and the difference is “the frequency of the right rear wheel is lower”; if the result is zero, it means that the frequencies are consistent.

[0131] In an embodiment, the right rear wheel is the target wheel, and the torque data of the right rear wheel is analyzed by frequency spectrum analysis to obtain a fluctuation frequency of 2 Hz (torque fluctuation frequency); the torque fluctuation frequency of the right front wheel is analyzed to be 3 Hz. The right side longitudinal wheel torque difference value is (the torque fluctuation frequency of the right front wheel , the torque fluctuation frequency of the right rear wheel ).

[0132] The torque fluctuation frequency of the right rear wheel is 2 Hz;

[0133] The torque fluctuation frequency difference is , so the feature is “the frequency of the right rear wheel is lower”.

[0134] Step 214, based on the torque fluctuation frequency and the torque fluctuation frequency difference, the frequency feature quadrant of the right rear wheel in the four-quadrant adaptive impedance is determined.

[0135] Further, the AMR robot determines the frequency characteristic quadrant of the right rear wheel based on the right rear wheel torque fluctuation frequency and the torque fluctuation frequency difference, combined with the frequency characteristic division rule of the four-quadrant adaptive impedance. The four-quadrant division takes the “torque fluctuation frequency” as the vertical axis (the frequency higher than the preset reference frequency is the positive direction, and lower than the reference frequency is the negative direction, and the reference frequency is set based on the average fluctuation frequency during normal driving, such as 2.5 Hz), and the “torque fluctuation frequency difference” as the horizontal axis (the right rear wheel frequency is higher as the positive direction, and lower as the negative direction): the first quadrant: the torque fluctuation frequency is higher than the reference frequency (vertical axis positive), and the right rear wheel frequency is higher (horizontal axis positive); the second quadrant: the torque fluctuation frequency is higher than the reference frequency (vertical axis positive), and the right rear wheel frequency is lower (horizontal axis negative); the third quadrant: the torque fluctuation frequency is lower than the reference frequency (vertical axis negative), and the right rear wheel frequency is lower (horizontal axis negative); the fourth quadrant: the torque fluctuation frequency is lower than the reference frequency (vertical axis negative), and the right rear wheel frequency is higher (horizontal axis positive).

[0136] Continue with the above example, the preset reference frequency is 2.5 Hz, the right rear wheel torque fluctuation frequency is 2 Hz (lower than the reference frequency, vertical axis negative direction), and the torque fluctuation frequency difference is “the right rear wheel frequency is lower” (horizontal axis negative direction), which meets the characteristics of the third quadrant, so the frequency characteristic quadrant of the right rear wheel in the four-quadrant adaptive impedance is the third quadrant.

[0137] Step 215, determine the torque transmission lag difference of the right rear wheel relative to the left rear wheel based on the lateral rear wheel torque difference value between the right rear wheel and the left rear wheel.

[0138] Further, the AMR robot determines the torque transmission lag difference of the right rear wheel relative to the left rear wheel based on the lateral rear wheel torque difference value (right rear wheel torque-left rear wheel torque) between the right rear wheel and the left rear wheel, combined with the transmission lag time of both to the torque command (the delay time from the generation of the drive command to the actual output of the torque). The transmission lag difference is calculated by “right rear wheel transmission lag time-left rear wheel transmission lag time”, and the result is positive, indicating that the right rear wheel lag time is longer, and the difference is “the right rear wheel lag is more significant”; the result is negative, indicating that the right rear wheel lag time is shorter, and the difference is “the left rear wheel lag is more significant”; the result is zero, indicating that the lag time is consistent. This difference reflects the timeliness difference of the torque transmission of the two rear wheels.

[0139] Continue with the above example, the lateral rear wheel torque difference value (right rear wheel-left rear wheel) is (right rear wheel , left rear wheel ). The right rear wheel transmission lag time is 0.03 s, and the left rear wheel transmission lag time is 0.02 s. The transmission lag difference = 0.03 s-0.02 s = 0.01 s>0, so the torque transmission lag difference of the right rear wheel relative to the left rear wheel is “the right rear wheel lag is more significant”.

[0140] Step 216, based on the diagonal wheel torque difference between the right rear wheel and the left front wheel, combined with the impedance adjustment strategy corresponding to the torque transmission hysteresis difference and the frequency characteristic quadrant, determine the final adaptive impedance adjustment parameter of the right rear wheel.

[0141] Further, the AMR robot first calculates the diagonal wheel torque difference (right rear wheel torque-left front wheel torque) of the right rear wheel and the left front wheel, and then combines the impedance adjustment strategy corresponding to the torque transmission hysteresis difference and the frequency characteristic quadrant (different quadrants have different stiffness, damping adjustment reference and dynamic coefficient), to determine the final adaptive impedance adjustment parameter of the right rear wheel. The specific logic is: the greater the absolute value of the diagonal torque difference, the more significant the right rear wheel transmission hysteresis, and if the frequency characteristic quadrant is a quadrant that needs to enhance impedance (such as the third quadrant), the increase of the impedance parameter relative to the reference value is greater (to suppress the slipping trend).

[0142] Continue with the above embodiment, the current torque of the right rear wheel , the torque of the left front wheel , the diagonal wheel torque difference is , and the absolute value is . Step 214 determines that the frequency characteristic quadrant is the third quadrant, and its impedance adjustment strategy is: the stiffness reference value , the damping reference value , and the increase coefficient is improved when the hysteresis is significant. The transmission hysteresis difference is that the right rear wheel hysteresis is more significant, and the corresponding adjustment coefficient is: the stiffness increase coefficient k1=0.5, and the damping increase coefficient k2=0.2, so the adaptive impedance adjustment parameter is:

[0143] The stiffness coefficient K=K0+the absolute value of the diagonal torque difference ;

[0144] The damping coefficient B=B0+the absolute value of the diagonal torque difference .

[0145] The embodiment of the application combines the frequency characteristics, transmission hysteresis difference and four-quadrant strategy to realize precise parameter configuration for the right rear wheel slipping trend, so that the impedance parameter can match the torque dynamic characteristics of the right rear wheel, and adapt to the torque imbalance state in the horizontal and diagonal directions, thereby improving the reliability of slip suppression and the running stability of the AMR robot in the working process.

[0146] Further, the AMR robot provided by the application is described below, and the AMR robot described below can be correspondingly referred to the anti-slip moving control method for the AMR robot described above.

[0147] Optionally, refer to Figure 2 , Figure 2is a structural schematic diagram of an AMR robot provided by the application, and the AMR robot comprises:

[0148] A slip monitoring module 210 is configured to determine a target wheel with a slip trend based on real-time driving torque of each wheel collected by a driving motor of the AMR robot.

[0149] An impedance adjustment module 220 is configured to determine an adaptive impedance adjustment parameter of the target wheel based on the four-quadrant adaptive impedance in combination with the current driving torque of the target wheel and a wheel torque difference value between adjacent wheels.

[0150] An impedance control module 230 is configured to apply corresponding impedance control to the driving motor of the target wheel based on the adaptive impedance adjustment parameter of the target wheel, so as to obtain an adjusted output torque of the target wheel.

[0151] A movement control module 240 is configured to adjust the movement posture and movement speed of the AMR robot based on the adjusted output torque until the AMR robot does not have a slip trend.

[0152] The embodiment of the application quickly locates the target wheel with a slip trend based on the slip trend judgment result, and deeply analyzes the stress characteristics of the target wheel in combination with the four-quadrant adaptive impedance, the current driving torque of the target wheel and the torque difference value, so that the determined adaptive impedance adjustment parameter has stronger working condition adaptability, the impedance control is applied to the driving motor of the target wheel according to the adaptive impedance adjustment parameter, the output torque of the target wheel can be more effectively adjusted to better meet the actual operation requirement, and finally the movement posture and movement speed of the robot are dynamically optimized by using the adjusted output torque to eliminate the slip trend, so that the stress of the robot in different working conditions can be comprehensively considered, and the running stability of the AMR robot in the operation process is improved.

[0153] Please refer to Figure 3 , Figure 3 An embodiment of an electronic device provided by the embodiment of the application is shown in the figure. Figure 3 As shown in the figure, the embodiment of the application provides an electronic device 300, which comprises a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and capable of running on the processor 320, and the processor 320 implements the following steps when executing the computer program 311:

[0154] Determine a target wheel with a slip trend based on real-time driving torque of each wheel collected by a driving motor of the AMR robot.

[0155] Determine an adaptive impedance adjustment parameter of the target wheel based on the four-quadrant adaptive impedance in combination with the current driving torque of the target wheel and a wheel torque difference value between adjacent wheels.

[0156] The adaptive impedance adjustment parameter of the target wheel is applied to the driving motor of the target wheel to exert corresponding impedance control, so as to obtain the adjusted output torque of the target wheel.

[0157] The moving posture and moving speed of the AMR robot are adjusted based on the adjusted output torque until the AMR robot has no slipping trend.

[0158] Please refer to Figure 4 , Figure 4 The embodiment of the computer readable storage medium provided by the embodiment of the present application is provided. As shown in Figure 4 , the embodiment provides a computer readable storage medium 400, which stores a computer program 311, and the computer program 311 is executed by a processor to implement the following steps:

[0159] Based on the real-time driving torque of each wheel collected by the driving motor of the AMR robot, the target wheel with a slipping trend is determined;

[0160] Based on the four-quadrant adaptive impedance combined with the current driving torque of the target wheel and the wheel torque difference value between adjacent wheels, the adaptive impedance adjustment parameter of the target wheel is determined;

[0161] The adaptive impedance adjustment parameter of the target wheel is applied to the driving motor of the target wheel to exert corresponding impedance control, so as to obtain the adjusted output torque of the target wheel.

[0162] The moving posture and moving speed of the AMR robot are adjusted based on the adjusted output torque until the AMR robot has no slipping trend.

[0163] In another aspect, the present application also provides a computer program product, which includes a computer program, the computer program can be stored on a non-transitory computer readable storage medium, and the computer program is executed by a processor, so that the computer can execute the anti-slip moving control method for the AMR robot provided by the above-mentioned methods, and the method includes:

[0164] Based on the real-time driving torque of each wheel collected by the driving motor of the AMR robot, the target wheel with a slipping trend is determined;

[0165] Based on the four-quadrant adaptive impedance combined with the current driving torque of the target wheel and the wheel torque difference value between adjacent wheels, the adaptive impedance adjustment parameter of the target wheel is determined;

[0166] The adaptive impedance adjustment parameter of the target wheel is applied to the driving motor of the target wheel to exert corresponding impedance control, so as to obtain the adjusted output torque of the target wheel.

[0167] The moving posture and moving speed of the AMR robot are adjusted based on the adjusted output torque until the AMR robot has no slipping trend.

[0168] The system embodiments described above are only illustrative, wherein the units described as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed to multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment scheme according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0169] Through the description of the above embodiments, those skilled in the art can clearly understand that the embodiments can be realized by means of software and the necessary general hardware platform, and of course can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0170] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A slip prevention movement control method for an AMR robot, characterized by, The method comprises: determining a target wheel with a tendency of slipping based on real-time driving torque of each wheel collected by a driving motor of an AMR robot; determining an adaptive impedance adjustment parameter of the target wheel based on four-quadrant adaptive impedance and a current driving torque of the target wheel and a wheel torque difference value between adjacent wheels; applying corresponding impedance control to the driving motor of the target wheel based on the adaptive impedance adjustment parameter of the target wheel to obtain an adjusted output torque of the target wheel; adjusting a moving posture and a moving speed of the AMR robot based on the adjusted output torque until the AMR robot has no tendency of slipping.

2. The anti-slip moving control method for an AMR robot according to claim 1, characterized in that, The method of determining the adaptive impedance adjustment parameter of the target wheel based on the four-quadrant adaptive impedance and the current driving torque of the target wheel and the wheel torque difference value between adjacent wheels comprises: if the target wheel is a left front wheel, determining a torque action direction of the left front wheel based on a current driving torque of the left front wheel and determining a torque advantage direction of the left front wheel relative to a right front wheel based on a horizontal front wheel torque difference value between the left front wheel and the right front wheel; determining a torque action quadrant of the left front wheel in the four-quadrant adaptive impedance based on the torque action direction and the torque advantage direction; determining a torque difference degree of the left front wheel relative to a left rear wheel based on a left side longitudinal wheel torque difference value between the left front wheel and the left rear wheel; determining the adaptive impedance adjustment parameter of the left front wheel based on a diagonal wheel torque difference value between the left front wheel and a right rear wheel, the torque difference degree and an impedance adjustment reference corresponding to the torque action quadrant.

3. The anti-slip moving control method for an AMR robot according to claim 1, characterized by, The method of determining the adaptive impedance adjustment parameter of the target wheel based on the four-quadrant adaptive impedance and the current driving torque of the target wheel and the wheel torque difference value between adjacent wheels comprises: if the target wheel is a right front wheel, obtaining a torque peak value feature of the right front wheel based on a current driving torque of the right front wheel and obtaining a torque peak value difference feature of the right front wheel relative to a right rear wheel based on a right side longitudinal wheel torque difference value between the right front wheel and the right rear wheel; determining a peak feature quadrant of the right front wheel in the four-quadrant adaptive impedance based on the torque peak value feature and the torque peak value difference feature; determining a torque transmission efficiency difference of the right front wheel relative to a left front wheel based on a horizontal front wheel torque difference value between the right front wheel and the left front wheel; determining the adaptive impedance adjustment parameter of the right front wheel based on a diagonal wheel torque difference value between the right front wheel and a left rear wheel, the torque transmission efficiency difference and an impedance adjustment strategy corresponding to the peak feature quadrant.

4. The anti-slip moving control method for an AMR robot according to claim 1, characterized by, The method of determining the adaptive impedance adjustment parameter of the target wheel based on the four-quadrant adaptive impedance and the current driving torque of the target wheel and the wheel torque difference value between adjacent wheels comprises: if the target wheel is a left rear wheel, extracting a torque change period of the left rear wheel based on a current driving torque of the left rear wheel and extracting a torque change period difference of the left rear wheel relative to a left front wheel based on a left side longitudinal wheel torque difference value between the left rear wheel and the left front wheel; determining a period feature quadrant of the left rear wheel in the four-quadrant adaptive impedance based on the torque change period and the torque change period difference; determine a torque response sensitivity difference of the left rear wheel relative to the right rear wheel based on a lateral rear wheel torque difference value between the left rear wheel and the right rear wheel; determine an adaptive impedance adjustment parameter of the left rear wheel based on a diagonal wheel torque difference value between the left rear wheel and the front left wheel in combination with the torque response sensitivity difference and an impedance adjustment strategy corresponding to the periodic characteristic quadrant.

5. The anti-slip mobile control method for an AMR robot according to claim 1, characterized by, determine the adaptive impedance adjustment parameter of the target wheel based on the four-quadrant adaptive impedance and a current driving torque of the target wheel and a wheel torque difference value between adjacent wheels, including: if the target wheel is the right rear wheel, identify a torque fluctuation frequency of the right rear wheel based on a current driving torque of the right rear wheel, and identify a torque fluctuation frequency difference of the right rear wheel relative to the front right wheel based on a right longitudinal wheel torque difference value between the right rear wheel and the front right wheel; determine a frequency characteristic quadrant of the right rear wheel in the four-quadrant adaptive impedance based on the torque fluctuation frequency and the torque fluctuation frequency difference; determine a torque transmission lag difference of the right rear wheel relative to the left rear wheel based on a lateral rear wheel torque difference value between the right rear wheel and the left rear wheel; determine a final adaptive impedance adjustment parameter of the right rear wheel based on a diagonal wheel torque difference value between the right rear wheel and the front right wheel in combination with the torque transmission lag difference and an impedance adjustment strategy corresponding to the frequency characteristic quadrant. 6.The anti-slip mobile control method for an AMR robot according to any one of claims 1 to 5, characterized in that, determine the target wheel with a tendency of slipping based on real-time driving torques of each wheel collected by driving motors of the AMR robot, including: determine a lateral front wheel torque difference value based on a difference between the real-time driving torque of the front left wheel and the real-time driving torque of the front right wheel, and determine a lateral rear wheel torque difference value based on a difference between the real-time driving torque of the rear left wheel and the real-time driving torque of the rear right wheel; determine a left longitudinal wheel torque difference value based on a difference between the real-time driving torque of the front left wheel and the real-time driving torque of the rear left wheel, and determine a right longitudinal wheel torque difference value based on a difference between the real-time driving torque of the front right wheel and the real-time driving torque of the rear right wheel; determine a vehicle lateral torque imbalance direction based on the lateral front wheel torque difference value and the lateral rear wheel torque difference value, and determine a vehicle longitudinal torque imbalance direction based on the left longitudinal wheel torque difference value and the right longitudinal wheel torque difference value; determine the target wheel with a tendency of slipping based on the vehicle lateral torque imbalance direction and the vehicle longitudinal torque imbalance direction.

7. The anti-slip mobile control method for an AMR robot according to claim 6, characterized by, determine the target wheel with a tendency of slipping based on the vehicle lateral torque imbalance direction and the vehicle longitudinal torque imbalance direction, including: perform direction superposition based on the vehicle lateral torque imbalance direction and the vehicle longitudinal torque imbalance direction to obtain a torque imbalance superposition direction; if the torque imbalance superposition direction is a front left direction, determine that the target wheel is the front left wheel; if the torque imbalance superposition direction is a front right direction, determine that the target wheel is the front right wheel; if the torque imbalance superposition direction is a rear left direction, determine that the target wheel is the rear left wheel; if the torque imbalance superposition direction is a rear right direction, determine that the target wheel is the rear right wheel.

8. An AMR robot, characterized in that, The anti-slip movement control method for the AMR robot according to any one of claims 1 to 7; the AMR robot comprises: a slip monitoring module, configured to determine a target wheel with a slip trend based on real-time driving torque of each wheel collected by a driving motor of the AMR robot; an impedance adjusting module, configured to determine an adaptive impedance adjusting parameter of the target wheel based on a four-quadrant adaptive impedance combined with a current driving torque of the target wheel and a wheel torque difference value between adjacent wheels; an impedance control module, configured to apply corresponding impedance control to the driving motor of the target wheel based on the adaptive impedance adjusting parameter of the target wheel, to obtain an adjusted output torque of the target wheel; a movement control module, configured to adjust a movement posture and a movement speed of the AMR robot based on the adjusted output torque, until the AMR robot has no slip trend.

9. An electronic device comprising: a memory, configured to store a computer software program; a processor, configured to read and execute the computer software program, wherein the processor, when executing the computer software program, implements the anti-slip movement control method for the AMR robot according to any one of claims 1 to 7.

10. A non-transitory computer readable storage medium having stored therein a computer software program, characterized in that, The computer software program, when executed by the processor, implements the anti-slip movement control method for the AMR robot according to any one of claims 1 to 7.

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