A robot walking module multi-motor synchronous speed regulation method, system and terminal

Abstract

The application provides a robot walking module multi-motor synchronous speed regulation method and system and a terminal, relates to the technical field of a robot walking module, and comprises the following steps: acquiring physical parameters of a robot, real-time angular velocity of a wheel and real-time forward speed; analyzing the physical parameters of the robot, the real-time angular velocity of the wheel and the real-time forward speed to determine a robot walking detection result; determining whether the robot walking detection result is a preset normal walking result or a preset abnormal walking result; if the result is the normal walking result, preset normal walking parameters are determined as robot walking parameters; if the result is the abnormal walking result, the real-time forward speed is analyzed to determine the robot walking parameters; the preset robot walking module is controlled to perform synchronous speed regulation on the preset motor according to the robot walking parameters, and the robot walking detection result is acquired for cyclic determination. The application has the effect of ensuring the stability of the robot walking module.

Description

Technical Field

[0001] This application relates to the technical field of robot walking modules, and in particular to a method, system and terminal for synchronous speed regulation of multiple motors in a robot walking module. Background Technology

[0002] The multi-motor synchronous speed control method for robot walking modules refers to a method that controls the operating parameters of multiple motors to enable the robot walking module to walk stably, with the aim of improving the walking stability of the robot walking module.

[0003] In related technologies, the method for synchronous speed regulation of motors in robot walking modules usually starts by generating initial commands for each motor through inverse kinematics solution, and collects the operating status of each motor in real time, calculates the speed deviation between each motor and all other motors, calculates the compensation amount of the motor based on the speed deviation, and finally inputs the compensation amount to the input terminal of the corresponding motor, so that the motor adjusts its output according to the operating status.

[0004] Regarding the aforementioned technologies, the compensation amount is superimposed on the input of the corresponding motor. However, if the robot's walking module gets stuck in a mud pit, the resistance of the mud pit will cause the wheels to slip or spin freely under the large torque after compensation, resulting in a decrease in the walking stability of the robot's walking module. There is still room for improvement. Summary of the Invention

[0005] To ensure the improved stability of the robot's walking module, this application provides a method, system, and terminal for synchronous speed regulation of multiple motors in a robot walking module.

[0006] In a first aspect, this application provides a method for synchronous speed regulation of multiple motors in a robot walking module, which adopts the following technical solution: A method for synchronous speed control of multiple motors in a robot walking module includes: Acquire robot physical parameters, real-time wheel angular velocity, and real-time forward speed; The robot's physical parameters, real-time wheel angular velocity, and real-time forward speed are analyzed to determine the robot's walking detection results; Determine whether the robot's walking detection result is a preset normal walking result or a preset abnormal walking result; If the result is a normal walking result, the preset normal walking parameters will be determined as the robot's walking parameters; If the walking result is abnormal, the real-time forward speed is analyzed to determine the robot's walking parameters; Based on the robot's walking parameters, the preset robot walking module is controlled to synchronously adjust the speed of the preset motors, and the robot walking detection results are obtained for cyclic judgment.

[0007] Optionally, the steps of analyzing the robot's physical parameters, real-time wheel angular velocity, and real-time forward speed to determine the robot's walking detection results include: Determine the robot wheel radius and the number of robot wheels based on the robot's physical parameters; Calculate the product of the real-time angular velocity of the wheel and the radius of the robot wheel to generate the linear velocity of the wheel; The average linear velocity of the wheels is calculated based on the number of robot wheels to generate an average equivalent ground velocity. The average equivalent ground velocity and real-time forward velocity are analyzed to determine the robot's walking detection results.

[0008] Optionally, the steps of analyzing the average equivalent ground velocity and real-time forward velocity to determine the robot's walking detection results include: Calculate the absolute value of the difference between the average equivalent ground speed and the real-time forward speed to generate the wheel speed deviation; Determine whether the wheel speed deviation and real-time forward speed meet the preset requirements for abnormal wheel movement; If the conditions are met, the preset abnormal walking result will be defined as the robot walking detection result; If it does not meet the requirements, the preset normal walking result will be defined as the robot walking detection result.

[0009] Optionally, the steps of analyzing the real-time forward velocity to determine the robot's walking parameters include: The preset initial swaying frequency and preset initial torque amplitude are input into the preset torque command function for solving to generate the motor torque command; The robot walking module is controlled to shake according to the preset number of shaking cycles and motor torque commands, and the shaking initiation time and shaking completion signal are obtained. The effective displacement of the machine is determined by analyzing the number of shaking cycles, the initial time of shaking, the initial frequency of shaking, and the real-time forward speed based on the shaking completion signal. The number of swaying cycles, the initial frequency of swaying, the initial amplitude of torque, and the effective displacement of the body are analyzed to determine the robot's walking parameters.

[0010] Optionally, the steps to analyze the number of swaying cycles, the initial swaying time, the initial swaying frequency, and the real-time forward speed to determine the effective displacement of the machine include: Calculate the quotient of the number of swaying cycles and the initial swaying frequency to generate the body swaying time; Calculate the sum of the initial shaking time and the shaking time of the machine body to generate the shaking completion time; The real-time forward velocity is integrated based on the initial time and completion time of the swaying to generate the effective displacement of the machine.

[0011] Optionally, the steps to analyze the number of swaying cycles, initial swaying frequency, initial torque amplitude, and effective body displacement to determine the robot's walking parameters include: Determine whether the effective displacement of the body is greater than the preset effective displacement threshold; If it is greater than the preset normal walking parameters, then the preset normal walking parameters will be defined as the robot walking parameters. If it is not greater than, then obtain the torque limit range; The number of swaying cycles, torque limit amplitude, initial swaying frequency, and initial torque amplitude are analyzed to determine the robot's walking parameters.

[0012] Optionally, the steps to analyze the number of swaying cycles, torque limit amplitude, initial swaying frequency, and initial torque amplitude to determine the robot's walking parameters include: Calculate the sum of the initial shaking frequency and the preset shaking frequency increment to generate the final shaking frequency; Calculate the sum of the initial torque magnitude and the preset torque magnitude increment to generate the torque adjustment magnitude; The torque adjustment range and torque limit range are sorted to determine the minimum torque range, and the minimum torque range is defined as the final torque range; The robot's walking parameters are generated by associating the number of swaying cycles, the final torque amplitude, the final swaying frequency, and preset general walking parameters.

[0013] Secondly, this application provides a multi-motor synchronous speed control system for a robot walking module, which adopts the following technical solution: A multi-motor synchronous speed control system for a robot walking module includes: The acquisition module is used to acquire robot physical parameters, real-time wheel angular velocity, real-time forward speed, and robot walking detection results. A memory for storing a program for a multi-motor synchronous speed control method for a robot walking module as described in any of the above claims; The processor and the program in the memory can be loaded and executed by the processor to implement a multi-motor synchronous speed control method for a robot walking module as described in any of the above.

[0014] Thirdly, this application provides a smart terminal, which adopts the following technical solution: A smart terminal includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as described in any of the preceding claims, a method for synchronous speed control of multiple motors in a robot walking module.

[0015] In summary, this application includes at least one of the following beneficial technical effects: 1. After analyzing the robot's physical parameters, real-time wheel angular velocity, and real-time forward speed, the robot's walking detection results are determined. When the robot's walking detection results are determined to be normal walking results, the normal walking parameters are directly defined as the robot's walking parameters. If the walking results are abnormal, the robot's walking parameters are determined after analyzing the real-time forward speed. Based on the robot's walking parameters, the robot's walking module is controlled to synchronously adjust the speed of the motors. When the robot's walking module is detected to be stuck in a mud pit, the output of each motor is controlled by adjusting the robot's walking parameters, causing the robot's walking module to sway back and forth in the mud pit. By using inertia to accumulate kinetic energy, the robot's walking module can be effectively prevented from slipping or spinning freely after compensation deviation, thereby ensuring the stability of the robot's walking module. 2. The linear velocity of the wheel is generated by calculating the product of the real-time angular velocity of the wheel and the radius of the robot wheel. The average value of the linear velocity of the wheel is then calculated based on the number of robot wheels to generate the average equivalent ground velocity. The robot walking detection results are determined by analyzing the average equivalent ground velocity and the real-time forward speed. The robot walking parameters are then adjusted according to the robot walking detection results to control the output of each motor, thereby effectively avoiding slippage or idling of the robot walking module and ensuring the stability of the robot walking module. 3. The wheel speed deviation is generated by calculating the absolute value of the difference between the average equivalent ground speed and the real-time forward speed. When the wheel speed deviation and the real-time forward speed meet the requirements for abnormal wheel movement, the abnormal movement result is directly defined as the robot movement detection result; if they do not meet the requirements, the normal movement result is defined as the robot movement detection result. Thus, based on the average equivalent ground speed of the wheel and the effective movement distance of the robot movement module, it is determined whether the robot movement module is stuck in the mud, thereby ensuring the effect of improving the movement stability of the robot movement module. Attached Figure Description

[0016] Figure 1 This is a flowchart of a multi-motor synchronous speed control method for a robot walking module according to an embodiment of this application.

[0017] Figure 2 This is a flowchart of the steps in this application embodiment to analyze the robot's physical parameters, real-time wheel angular velocity, and real-time forward speed to determine the robot's walking detection results.

[0018] Figure 3 This is a flowchart illustrating the steps in this application embodiment to analyze the average equivalent ground speed and real-time forward speed to determine the robot's walking detection results.

[0019] Figure 4 This is a flowchart illustrating the steps in this application embodiment to analyze the real-time forward speed to determine the robot's walking parameters.

[0020] Figure 5 This is a flowchart illustrating the steps in this application embodiment to analyze the number of swaying cycles, the initial swaying time, the initial swaying frequency, and the real-time forward speed to determine the effective displacement of the machine body.

[0021] Figure 6 This is a flowchart illustrating the steps in this application to analyze the number of swaying cycles, the initial swaying frequency, the initial torque amplitude, and the effective displacement of the body to determine the robot's walking parameters.

[0022] Figure 7 This is a flowchart illustrating the steps in this application embodiment to analyze the number of swaying cycles, torque limit amplitude, initial swaying frequency, and initial torque amplitude to determine the robot's walking parameters. Detailed Implementation

[0023] To make the purpose, technical solution, and advantages of this application clearer, the following description is provided in conjunction with the appendix. Figures 1 to 7 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0024] This application discloses a method for synchronous speed control of multiple motors in a robot walking module. Specifically, it discloses a robot walking module and a processing terminal. The processing terminal is communicatively connected to the robot walking module to achieve data interaction and control. After the processing terminal acquires the robot's physical parameters, real-time wheel angular velocity, and real-time forward speed, it analyzes these parameters to determine the robot walking detection result. If the robot walking detection result is normal, the normal walking parameters are directly defined as the robot walking parameters. If the result is abnormal, the real-time forward speed is analyzed to determine the robot walking parameters. Based on these parameters, the robot walking module is controlled to synchronously adjust the speed of the motors. When the robot walking module is detected to be stuck in mud, the output of each motor is controlled by adjusting the robot's walking parameters, causing the robot walking module to sway back and forth in the mud, accumulating kinetic energy through inertia. This effectively avoids slippage or idling after compensation deviation, thereby ensuring improved stability of the robot walking module.

[0025] Reference Figure 1 This application discloses a method for synchronous speed regulation of multiple motors in a robot walking module, comprising the following steps: Step S100: Obtain the robot's physical parameters, real-time wheel angular velocity, and real-time forward speed.

[0026] The robot's physical parameters refer to the physical parameters of the robot's locomotion module, including the robot wheel radius and the number of wheels, which are obtained by the operator from the specifications provided by the robot locomotion module manufacturer. The robot wheel radius is strongly correlated with the wheel's linear velocity; the wheel radius is the radius of the circular path the wheel travels. A larger wheel radius results in a higher wheel linear velocity. Conversely, the number of wheels is strongly correlated with the average equivalent ground velocity; a larger number of wheels results in a lower average equivalent ground velocity. This provides data support for subsequently determining the wheel linear velocity and the average equivalent ground velocity.

[0027] Real-time wheel angular velocity is a value that measures the speed at which the wheels of the robot's walking module rotate. It is read by the processing terminal from the encoder installed on each motor. Real-time wheel angular velocity is strongly correlated with wheel linear velocity; the higher the real-time wheel angular velocity, the higher the wheel linear velocity, thus providing data support for subsequent determination of wheel linear velocity.

[0028] Real-time forward speed refers to the forward speed of the robot's walking module, which is read from the inertial measurement unit by the processing terminal. By determining the real-time forward speed, the current walking speed of the robot's walking module can be determined. If the walking speed is too slow, it indicates that the wheels may be stuck in mud, thus providing data support for subsequent determination of the robot's walking detection results.

[0029] Step S101: Analyze the robot's physical parameters, real-time wheel angular velocity, and real-time forward speed to determine the robot's walking detection results.

[0030] The robot walking detection result refers to the detection result of whether the robot walking module is stuck in mud, including normal walking results and abnormal walking results. It is obtained by the processing terminal after analyzing the robot's physical parameters, real-time wheel angular velocity, and real-time forward speed. The specific method is described in [reference needed]. Figure 2 The steps are as follows: By determining the robot's walking detection results, when the robot's walking module is detected to be stuck in a mud pit, the walking parameters of the robot are adjusted to control the output of each motor, causing the robot's walking module to sway back and forth in the mud pit. This effectively avoids the robot's walking module slipping or spinning freely, thereby ensuring and improving the stability of the robot's walking module.

[0031] Step S102: Determine whether the robot's walking detection result is a preset normal walking result or a preset abnormal walking result.

[0032] Among them, the normal walking result refers to the detection result that the robot's walking module did not get stuck in the mud pit, which is stored by the operator in the processing terminal.

[0033] Abnormal walking results refer to the detection results of the robot's walking module getting stuck in a mud pit, which are stored by the operator in the processing terminal.

[0034] By determining whether the robot's walking detection result is normal or abnormal, it can be determined whether the current robot walking module is stuck in a mud pit. This allows for the determination of the robot's walking parameters based on the walking detection results, thereby ensuring the stability of the robot walking module's walking.

[0035] Step S1021: If the result is normal walking, then the preset normal walking parameters are determined as the robot walking parameters.

[0036] If the robot's walking detection result is normal, it means that the robot's walking module is not stuck in the mud. Therefore, the processing terminal directly determines the normal walking result as the robot's walking parameter, so as to control the robot's walking module to synchronously adjust the speed of the motor, thereby ensuring the effect of improving the stability of the robot's walking module.

[0037] Normal walking parameters refer to the walking parameters of the robot's walking module when it is not stuck in mud, such as the desired forward speed of the robot's walking module and the output power of the motor, which are set in advance by the operator. By determining the normal walking parameters, the control parameters of the robot's walking module during normal walking can be determined, so as to facilitate subsequent control of the robot's walking module to synchronize the speed of the motor.

[0038] Robot walking parameters refer to the control parameters of the robot walking module during movement. These include walking parameters for both mud-covered and non-mud-covered conditions, such as normal walking parameters, number of swaying cycles, final torque amplitude, final swaying frequency, and general walking parameters. These are obtained by the processing terminal after determining the normal walking parameters as the robot walking parameters. By determining the robot walking parameters, and based on the robot walking detection results of the robot walking module, the walking parameters for different working conditions are determined to facilitate subsequent control of the robot walking module to synchronize the motor speed.

[0039] Step S1022: If the walking result is abnormal, the real-time forward speed is analyzed to determine the robot's walking parameters.

[0040] If the robot's walking detection result is abnormal, it means that the robot's walking module is stuck in mud. Compensation based on the speed deviations between the motors would cause the robot's walking module to slip or spin freely. Therefore, the processing terminal analyzes the real-time forward speed to determine the robot's walking parameters. The specific method is described in [reference needed]. Figure 4The steps are as follows: By determining the robot's walking parameters, when the robot's walking module is detected to be stuck in a mud pit, the output of each motor is controlled by adjusting the robot's walking parameters, causing the robot's walking module to sway back and forth in the mud pit. This effectively avoids the robot's walking module slipping or spinning freely, thereby ensuring and improving the stability of the robot's walking module.

[0041] The robot's walking parameters in this step are the same as those in step S1021. The difference is that in this step, the robot's walking parameters are obtained by the processing terminal after analyzing the real-time forward speed.

[0042] Step S103: Control the preset robot walking module to synchronously adjust the speed of the preset motor according to the robot walking parameters, and obtain the robot walking detection results for cyclic judgment.

[0043] After determining the robot's walking parameters, the processing terminal controls the robot's walking module to synchronously adjust the speed of the motor based on the robot's walking parameters, and obtains the robot's walking detection results for cyclic judgment. In this way, the motor speed is synchronously adjusted according to whether the robot's walking module is stuck in the mud, thereby effectively avoiding the occurrence of unstable walking due to the robot's walking module being stuck in the mud.

[0044] A robot walking module refers to a mobile robot with multiple wheels on its chassis. It consists of servo motors, reducers, wheels, encoders, timers, and inertial measurement units. Each wheel is equipped with a motor, reducer, and encoder. The motor provides power to the robot walking module, converting electrical energy into mechanical energy. The reducer provides sufficient grip for the robot walking module. The wheel is the part that directly contacts the ground and moves the robot walking module by rotating. The encoder measures the real-time angular velocity of the wheel, the timer records time-related parameters during the operation of the robot walking module, and the inertial measurement unit measures the robot's real-time forward speed.

[0045] The motor is a component used to convert electrical energy into mechanical energy in the robot's walking module. The specific model is determined by the operator based on the actual situation. The motor is used to provide forward power for the robot's walking module.

[0046] Reference Figure 2 The steps for analyzing the robot's physical parameters, real-time wheel angular velocity, and real-time forward speed to determine the robot's walking detection results include: Step S200: Determine the robot wheel radius and the number of robot wheels based on the robot's physical parameters.

[0047] The robot wheel radius refers to the radius of the robot wheel, which is identified and retrieved from the robot's physical parameters by the processing terminal. The robot wheel radius and wheel linear velocity are strongly correlated; the larger the robot wheel radius, the greater the wheel linear velocity, thus providing data support for subsequent determination of the wheel linear velocity.

[0048] The number of robot wheels refers to the number of wheels in the robot's walking module, which is identified and retrieved by the processing terminal from the robot's physical parameters. The number of robot wheels is strongly correlated with the average equivalent ground speed. When the number of robot wheels is larger, it means that the robot's walking module has more wheels, resulting in a smaller average speed allocated to each wheel, and thus a smaller average equivalent ground speed. This provides data support for subsequent determination of the average equivalent ground speed.

[0049] Step S201: Calculate the product of the real-time angular velocity of the wheel and the radius of the robot wheel to generate the linear velocity of the wheel.

[0050] The wheel linear velocity refers to the ground linear velocity generated by the wheel rolling on the ground, which is obtained by the processing terminal calculating the product of the real-time angular velocity of the wheel and the radius of the robot wheel. Under the condition that the radius of the robot wheel remains unchanged, the larger the real-time angular velocity of the wheel, the faster the rotation speed of the robot's walking module wheel is, and therefore the greater the ground linear velocity and the greater the wheel linear velocity, so as to facilitate the subsequent determination of the average equivalent ground velocity.

[0051] Step S202: Calculate the average value of the wheel linear velocity based on the number of robot wheels to generate the average equivalent ground velocity.

[0052] The average equivalent ground speed refers to the average ground linear speed of the current robot's walking module wheels. It is obtained by the processing terminal calculating the average of the wheel linear speeds based on the number of robot wheels, and can be expressed as follows: ,in Indicates the average equivalent ground velocity. Indicates the linear velocity of the wheel. Indicates the number of robot wheels. This represents the sum of the linear velocities of all wheels in the robot's walking module. Under the condition that the number of robot wheels remains constant, the greater the linear velocity of the wheels, the greater the linear velocity of the ground generated by the wheels rolling on the ground, and thus the greater the average equivalent ground velocity, thereby providing data support for the subsequent determination of robot walking detection results.

[0053] Step S203: Analyze the average equivalent ground speed and real-time forward speed to determine the robot walking detection results.

[0054] After determining the average equivalent ground velocity, the processing terminal analyzes the average equivalent ground velocity and the real-time forward velocity to obtain the robot's walking detection results. The specific method is described in [reference needed]. Figure 3 The steps are as follows: By determining the robot's walking detection results, when the robot's walking module is detected to be stuck in a mud pit, the walking parameters of the robot are adjusted to control the output of each motor, causing the robot's walking module to sway back and forth in the mud pit. This effectively avoids the robot's walking module slipping or spinning freely, thereby ensuring and improving the stability of the robot's walking module.

[0055] Reference Figure 3 The steps for analyzing the average equivalent ground velocity and real-time forward velocity to determine the robot's walking detection results include: Step S300: Calculate the absolute value of the difference between the average equivalent ground speed and the real-time forward speed to generate the wheel speed deviation.

[0056] Wheel speed deviation refers to the deviation between the linear velocity of the wheels on the ground and the actual forward speed of the robot's walking module. It is obtained by the processing terminal calculating the absolute value of the difference between the average equivalent ground speed and the real-time forward speed. When the wheel speed deviation is larger, it indicates that the wheel's rotational speed is higher than the actual moving speed of the robot's walking module. In this case, the wheels may get stuck in mud and slip, thus providing data support for subsequent determination of the robot's walking detection results.

[0057] Step S301: Determine whether the wheel speed deviation and real-time forward speed meet the preset requirements for abnormal wheel movement.

[0058] The requirement for normal wheel movement is that the wheel speed deviation is greater than a preset baseline speed deviation and the real-time forward speed is greater than a preset baseline forward speed, which is set in advance by the operator. By judging whether the two events of wheel speed deviation being greater than the baseline speed deviation and real-time forward speed being greater than the baseline forward speed occur simultaneously, it is determined whether the current robot walking module is stuck in a mud pit, so as to confirm the robot walking detection results.

[0059] In this step, the reference speed deviation refers to the critical state between the robot's walking module's normal walking state and its being stuck in a mud pit. This deviation is obtained by the operator beforehand through calibration experiments. The calibration experiment is first conducted on a flat surface free of mud. The robot walking module is allowed to walk steadily in a straight line at different speeds, and the difference between the average equivalent ground speed of the wheels and the real-time forward speed is recorded for each step. The maximum value among these differences is selected as the maximum measurement error under normal walking conditions. Subsequently, the robot walking module is allowed to walk on a muddy road. When the robot walking module gets stuck in a mud pit, the difference between the average equivalent ground speed of the wheels and the real-time forward speed is again recorded. Finally, the value among the differences that is greater than and closest to the maximum measurement error when the robot walking module is walking on a muddy road is selected as the reference speed deviation.

[0060] The reference forward speed is a small speed threshold set in advance by the operator to ensure that the wheels are attempting to turn, rather than remaining completely stationary. By determining the reference speed deviation and the reference forward speed, a benchmark for judging normal wheel movement is established, facilitating subsequent determination of the robot's movement detection results.

[0061] Step S3011: If the condition is met, the preset abnormal walking result is defined as the robot walking detection result.

[0062] If both the wheel speed deviation and the real-time forward speed are greater than the reference speed deviation and the real-time forward speed are greater than the reference forward speed, it means that the average rotational speed of the wheel is much higher than the actual forward speed of the robot walking module on the ground, and the robot walking module is not completely stationary. At this time, the robot walking module is spinning or slipping. The processing terminal directly defines the abnormal walking result as the robot walking detection result, so as to determine the robot walking parameters based on the robot walking detection result.

[0063] In step S3012, if the condition is not met, the preset normal walking result is defined as the robot walking detection result.

[0064] If the events of wheel speed deviation being greater than reference speed deviation and real-time forward speed being greater than reference forward speed do not occur simultaneously, it indicates that the robot walking module is not stuck in the mud. In this case, the processing terminal directly defines the normal walking result as the robot walking detection result, so that the robot walking parameters can be determined based on the robot walking detection result.

[0065] Reference Figure 4 The steps for analyzing real-time forward speed to determine the robot's walking parameters include: In step S400, the preset initial swaying frequency and the preset initial torque amplitude are input into the preset torque command function for solving to generate the motor torque command.

[0066] Among them, the motor torque command refers to the torque command output by the robot walking module. It is obtained by the processing terminal after inputting the initial swaying frequency and the initial torque amplitude into the torque command function. This allows the robot walking module to switch between positive and negative torque, realizing alternating torque output. This causes the robot walking module to accumulate kinetic energy by swaying back and forth, thereby getting out of the mud pit and ensuring the stability of the robot walking module.

[0067] The initial swaying frequency refers to the speed at which the robot's walking module sways back and forth when alternating torque outputs. It is obtained by the operator through calibration experiments in advance to facilitate subsequent control of the robot's walking module to sway.

[0068] The initial torque amplitude refers to the intensity of the robot's walking module's back-and-forth swaying when alternating torque output. It is obtained by the operator through calibration experiments in advance to facilitate subsequent control of the robot's walking module to sway.

[0069] In this step, the initial swaying frequency and initial torque amplitude are obtained through the same calibration test. First, the robot walking module is made to walk on a muddy road and then get stuck in a mud pit. The swaying frequency and torque amplitude within the allowable range of the robot walking module are arranged and combined. The robot walking module is then made to perform a forward and backward swaying mode under each combination. The effective displacement of the robot walking module is detected, and the minimum number of swaying cycles that allows the robot walking module to get out of the mud pit and walk normally is recorded. Finally, each combination and the corresponding number of swaying cycles are analyzed, and a combination that can quickly get out of the mud pit and walk normally with fewer swaying cycles is selected as the initial swaying frequency, initial torque amplitude, and number of swaying cycles.

[0070] The torque command function is a function used to calculate the torque command output by the robot's walking module. It is stored by the operator in the processing terminal and can be represented as follows: ,in This indicates the motor torque command. Indicates the initial magnitude of torque. Indicates the initial frequency of the shaking. The current running time is indicated by the processing terminal reading it from the system's timer. The torque command function first calculates a sine wave signal based on the initial swaying frequency and the current running time. Then, the sine wave signal is fed into a sign function. When the sine wave is positive, the value of the sign function is +1, and when the sine wave is negative, the value of the sign function is -1. Finally, the value of the sign function is multiplied by the initial torque amplitude to obtain a torque command that alternates between positive and negative initial torque amplitude values, so as to facilitate the subsequent control of the robot's walking module to sway.

[0071] Step S401: Control the preset robot walking module to shake according to the preset number of shaking cycles and motor torque command, and obtain the shaking start time and shaking completion signal.

[0072] After determining the motor torque command, the processing terminal controls the robot's walking module to shake according to the number of shaking cycles and the motor torque command. This causes the robot's walking module to control each motor to alternately execute the torque command between the positive and negative values ​​of the initial torque amplitude, shaking back and forth to accumulate kinetic energy, thereby attempting to get out of the mud pit, and obtaining the initial shaking time and shaking completion signal, so as to determine the effective displacement of the robot body in the future.

[0073] The number of swaying cycles refers to the number of back-and-forth swaying cycles performed by the robot's walking module, which is obtained through calibration tests conducted by the operator beforehand. The calibration test for determining the number of swaying cycles in this step is consistent with the calibration test in step S400. By determining the number of swaying cycles, the number of back-and-forth swaying cycles of the robot's walking module is determined, enabling the robot to sway back and forth when stuck in mud to attempt to escape, thereby ensuring improved walking stability.

[0074] The robot walking module in this step is the same as the robot walking module in step S103.

[0075] The initial swaying time refers to the time when the robot's walking module begins to sway, which is read by the processing terminal from the system's timer. By determining the initial swaying time, the effective displacement of the robot body can be determined based on the initial swaying time, the initial swaying frequency, and the implemented forward speed, thus providing data support for subsequent determination of the effective displacement of the robot body.

[0076] The shaking completion signal indicates that the robot's walking module has completed its shaking motion. Once the shaking is complete, the robot sends a signal representing the shaking completion to the processing terminal. By acquiring this shaking completion signal, it is determined that the robot's walking module has completed its shaking motion, which is then used to determine the effective displacement of the robot body.

[0077] Step S402: Based on the shaking completion signal, analyze the number of shaking cycles, shaking initial time, shaking initial frequency, and real-time forward speed to determine the effective displacement of the machine body.

[0078] Upon receiving the shaking completion signal, the processing terminal responds to the signal by analyzing the number of shaking cycles, the initial shaking time, the initial shaking frequency, and the real-time forward velocity to determine the effective displacement of the base. The specific method is described in [reference needed]. Figure 5 The steps are as follows: By determining the effective displacement of the machine body, it is determined whether the robot's walking module has generated an effective displacement after the shaking is completed, and then it is determined whether the robot's walking module has gotten out of the mud pit, so as to ensure the effect of improving the walking stability of the robot's walking module.

[0079] The effective displacement of the robot body refers to the effective distance traveled by the robot's walking module after shaking, relative to before shaking. It is obtained by the processing terminal after analyzing the number of shaking cycles, the initial shaking time, the initial shaking frequency, and the real-time forward speed. By determining the effective displacement of the robot body, it is possible to determine whether the robot's walking module has generated an effective displacement after shaking, and thus whether the robot's walking module has escaped the mud pit.

[0080] Step S403 involves analyzing the number of swaying cycles, the initial swaying frequency, the initial torque amplitude, and the effective displacement of the robot body to determine the robot's walking parameters.

[0081] After determining the effective displacement of the robot body, the processing terminal analyzes the number of swaying cycles, the initial swaying frequency, the initial torque amplitude, and the effective displacement of the robot body to determine the robot's walking parameters. The specific method is described in [reference needed]. Figure 6 The steps involve determining the robot's walking parameters to detect whether the robot's walking module has dislodged itself from the mud pit after its first wobbling, thereby ensuring the improved walking stability of the robot's walking module.

[0082] Reference Figure 5 The steps to determine the effective displacement of the machine body by analyzing the number of swaying cycles, the initial swaying time, the initial swaying frequency, and the real-time forward speed include: Step S500: Calculate the quotient of the number of swaying cycles and the initial swaying frequency to generate the body swaying time.

[0083] The body swaying time refers to the duration of the robot's walking module's swaying, which is obtained by the processing terminal calculating the quotient of the number of swaying cycles and the initial swaying frequency. With a constant number of swaying cycles, a higher initial swaying frequency indicates a faster forward and backward swaying speed of the robot's walking module, resulting in a shorter body swaying time, which facilitates the subsequent determination of the swaying completion time.

[0084] Step S501: Calculate the sum of the initial shaking time and the shaking time of the machine body to generate the shaking completion time.

[0085] The swaying completion time refers to the end time of the robot's swaying motion, which is obtained by the processing terminal by calculating the sum of the swaying initiation time and the swaying time of the robot body. By determining the swaying completion time, the moment when the robot's swaying motion is completed can be determined, so as to subsequently determine the effective displacement of the robot's body by combining it with the swaying initiation time.

[0086] Step S502: Integrate the real-time forward velocity based on the initial time of the swaying and the completion time of the swaying to generate the effective displacement of the machine body.

[0087] After determining the completion time of the swaying motion, the processing terminal integrates the real-time forward velocity based on the initial and completion times of the swaying motion to obtain the effective displacement of the machine body, which can be expressed as: ,in Indicates the effective displacement of the body. Indicates the initial time of the shaking. Indicates the time it takes for the shaking to complete. Indicates at time The real-time forward speed of the robot's walking module is integrated and accumulated over the shaking time to obtain the total displacement of the robot's walking module. This allows for subsequent determination of whether the robot's walking module has dislodged itself from the mud pit after the initial shaking, thereby ensuring the improvement of the robot's walking stability.

[0088] Reference Figure 6 The steps to determine the robot's walking parameters by analyzing the number of swaying cycles, the initial swaying frequency, the initial torque amplitude, and the effective displacement of the machine body include: Step S600: Determine whether the effective displacement of the body is greater than the preset effective displacement threshold.

[0089] The effective displacement threshold is a measure of the distance the robot can move to escape the mud pit after generating an effective displacement distance during shaking. It is preset by the operator. By determining whether the effective displacement of the robot body is greater than the effective displacement threshold, it is determined whether the robot's walking module has escaped the mud pit after the initial shaking. This allows the shaking to stop promptly after the robot has escaped the mud pit, improving the walking efficiency of the robot's walking module and facilitating the subsequent determination of robot walking parameters.

[0090] Step S6001: If the value is greater than the preset normal walking parameters, then the preset normal walking parameters are defined as robot walking parameters.

[0091] If the effective displacement of the robot body is greater than the effective displacement threshold, it means that the current robot walking module has generated an effective movement distance and has escaped the mud pit. Therefore, the processing terminal directly defines the normal walking parameters as the robot walking parameters, so that the robot walking module can be controlled to synchronously adjust the speed of each motor according to the robot walking parameters, thereby ensuring and improving the stability of the robot walking module's walking.

[0092] The normal walking parameters in this step are the same as those in step S1021.

[0093] Step S6002: If it is not greater than, then obtain the torque limit range.

[0094] If the effective displacement of the robot body is not greater than the effective displacement threshold, it means that the robot walking module has not generated an effective movement distance after the initial shaking and is still stuck in the mud. Therefore, it cannot be controlled with normal walking parameters. At this time, the processing terminal obtains the torque limit amplitude in order to determine the robot walking parameters in the future.

[0095] The torque limit range refers to the upper limit of the torque command that the motor is allowed to output, which is found by the operator in the specifications provided by the robot's walking module manufacturer. By determining the torque limit range, the motor output can be adjusted without damaging the motor, thereby effectively preventing damage to the motor due to high load operation.

[0096] Step S60021: Analyze the number of swaying cycles, torque limit amplitude, initial swaying frequency, and initial torque amplitude to determine the robot's walking parameters.

[0097] After determining the torque limit, the processing terminal analyzes the number of swaying cycles, the torque limit, the initial swaying frequency, and the initial torque amplitude to determine the robot's walking parameters. The specific method is described in [reference needed]. Figure 7 The steps involve adjusting the motor output during the initial shaking before the robot leaves the mud pit, thereby controlling the output of each motor to allow the robot to accumulate kinetic energy by shaking back and forth.

[0098] The robot walking parameters in this step are the same as those in step S6001. The difference is that the robot walking parameters in this step are obtained by the processing terminal after analyzing the number of swaying cycles, torque limit amplitude, initial swaying frequency, and initial torque amplitude.

[0099] Reference Figure 7 The steps to determine the robot's walking parameters by analyzing the number of swaying cycles, torque limit amplitude, initial swaying frequency, and initial torque amplitude include: Step S700: Calculate the sum of the initial shaking frequency and the preset shaking frequency increment to generate the final shaking frequency.

[0100] The final sway frequency refers to the frequency adjusted after the robot's walking module fails to leave the mud pit following the initial sway, and is calculated by the processing terminal as the sum of the initial sway frequency and the sway frequency increment. By determining the final sway frequency, the initial sway frequency is enhanced, facilitating subsequent synchronous adjustment of the output of each motor and thus improving the stability of the robot's walking module.

[0101] The swaying frequency increment refers to the increment in swaying frequency adjustment after the robot's walking module has not yet escaped the mud pit after its initial sway. It is preset by the operator. The operator determines the magnitude of the swaying frequency increment based on the road environment level in which the robot's walking module is located. First, the operator assesses the road environment by observing the robot's walking module, that is, assesses the mud level of the road. After the assessment, a mapping table is formed between the road environment level and the swaying frequency increment. When the mud level is higher, the swaying frequency increment is higher, so as to ensure that the robot's walking module can accumulate effective kinetic energy, thereby ensuring the effect of improving the walking stability of the robot's walking module.

[0102] Step S701: Calculate the sum of the initial torque amplitude and the preset torque amplitude increment to generate the torque adjustment amplitude.

[0103] The torque adjustment amplitude refers to the value obtained after adjusting the initial torque amplitude after the robot's walking module has not yet left the mud pit after its initial wobbling. It is calculated by the processing terminal as the sum of the initial torque amplitude and the torque amplitude increment. By determining the torque adjustment amplitude, the amplitude of the forward and backward wobbling is increased when the robot's walking module has not yet left the mud pit after its initial wobbling, thereby ensuring improved stability of the robot's walking module. The intensity of the forward and backward wobbling of the robot's walking module during alternating torque output.

[0104] The torque amplitude increment refers to the increment of the initial torque adjustment after the robot's walking module has not yet escaped the mud pit after its first wobbling. It is preset by the operator. The operator determines the magnitude of the torque amplitude increment based on the road environment level in which the robot's walking module is located. First, the operator evaluates the road environment in which the robot's walking module is located by observation, that is, assesses the mud level of the road. After the evaluation, a mapping table is formed to correspond the road environment level with the torque amplitude increment. When the mud level is higher, the torque amplitude increment is higher, so as to ensure that the robot's walking module can accumulate effective kinetic energy, thereby ensuring the effect of improving the walking stability of the robot's walking module.

[0105] Step S702: Sort the torque adjustment range and torque limit range to determine the minimum torque range, and define the minimum torque range as the final torque range.

[0106] The final torque amplitude refers to the value obtained after limiting the torque adjustment range according to the physical limitations of the robot's motors. The processing terminal sorts the torque adjustment ranges and torque limit ranges to obtain the minimum torque amplitude, which is then defined as the final torque amplitude. By determining the final torque amplitude, the output of each motor can be adjusted without damaging the motors, thereby ensuring improved stability of the robot's walking module.

[0107] The minimum torque amplitude refers to the minimum value between the torque adjustment amplitude and the torque limit amplitude, which is obtained by the processing terminal after sorting the torque adjustment amplitude and the torque limit amplitude. By determining the minimum torque amplitude, it is ensured that the torque amplitude of the motor does not exceed the upper limit of the torque command allowed to be output by the motor, thereby ensuring that the output of each motor can be adjusted without damaging the motor, thus improving the stability of the robot's walking module.

[0108] Step S703: Associate the number of swaying cycles, the final torque amplitude, the final swaying frequency, and the preset general walking parameters to generate robot walking parameters.

[0109] After determining the final torque amplitude, the robot's walking parameters are obtained by processing the number of associated swaying cycles, the final torque amplitude, the final swaying frequency, and general walking parameters. This allows the output of each motor to be increased when the robot's walking module has not yet left the mud pit during its first sway, causing the robot to sway back and forth again, thereby ensuring and improving the stability of the robot's walking module.

[0110] General walking parameters refer to the parameters that remain unchanged regardless of whether the robot's walking module is stuck in mud. For example, the robot's desired walking speed is set in advance by the operator. By determining the general walking parameters, only the output of each motor needs to be adjusted, thereby ensuring the stability of the robot's walking module.

[0111] Based on the same inventive concept, embodiments of this application provide a multi-motor synchronous speed control system for a robot walking module, including: The acquisition module is used to acquire robot physical parameters, real-time wheel angular velocity, real-time forward speed, robot walking detection results, swaying initiation time, swaying completion signal, and torque limit amplitude. The memory is used to store a program for a method of synchronous speed control of multiple motors in a robot walking module; The processor and memory can load and execute programs to implement a method for synchronous speed control of multiple motors in a robot walking module.

[0112] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0113] This application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed as a method for synchronous speed control of multiple motors in a robot walking module.

[0114] Computer storage media include, for example, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media that can store program code.

[0115] Based on the same inventive concept, this application provides an intelligent terminal, including a memory and a processor. The memory stores a computer program that can be loaded and executed by the processor to provide a method for synchronous speed regulation of multiple motors in a robot walking module.

[0116] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0117] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. A method for synchronous speed regulation of multiple motors in a robot walking module, characterized in that, include: Acquire robot physical parameters, real-time wheel angular velocity, and real-time forward speed; The robot's physical parameters, real-time wheel angular velocity, and real-time forward speed are analyzed to determine the robot's walking detection results; Determine whether the robot's walking detection result is a preset normal walking result or a preset abnormal walking result; If the result is a normal walking result, the preset normal walking parameters will be determined as the robot's walking parameters; If the walking result is abnormal, the real-time forward speed is analyzed to determine the robot's walking parameters; Based on the robot's walking parameters, the preset robot walking module is controlled to synchronously adjust the speed of the preset motors, and the robot walking detection results are obtained for cyclic judgment.

2. The method for synchronous speed regulation of multiple motors in a robot walking module according to claim 1, characterized in that, The steps for analyzing the robot's physical parameters, real-time wheel angular velocity, and real-time forward speed to determine the robot's walking detection results include: Determine the robot wheel radius and the number of robot wheels based on the robot's physical parameters; Calculate the product of the real-time angular velocity of the wheel and the radius of the robot wheel to generate the linear velocity of the wheel; The average linear velocity of the wheels is calculated based on the number of robot wheels to generate an average equivalent ground velocity. The average equivalent ground velocity and real-time forward velocity are analyzed to determine the robot's walking detection results.

3. The method for synchronous speed regulation of multiple motors in a robot walking module according to claim 2, characterized in that, The steps for analyzing the average equivalent ground velocity and real-time forward velocity to determine the robot's walking detection results include: Calculate the absolute value of the difference between the average equivalent ground speed and the real-time forward speed to generate the wheel speed deviation; Determine whether the wheel speed deviation and real-time forward speed meet the preset requirements for abnormal wheel movement; If the conditions are met, the preset abnormal walking result will be defined as the robot walking detection result; If it does not meet the requirements, the preset normal walking result will be defined as the robot walking detection result.

4. The method for synchronous speed regulation of multiple motors in a robot walking module according to claim 1, characterized in that, The steps for analyzing real-time forward velocity to determine robot walking parameters include: The preset initial swaying frequency and preset initial torque amplitude are input into the preset torque command function for solving to generate the motor torque command; The robot walking module is controlled to shake according to the preset number of shaking cycles and motor torque commands, and the shaking initiation time and shaking completion signal are obtained. The effective displacement of the machine is determined by analyzing the number of shaking cycles, the initial time of shaking, the initial frequency of shaking, and the real-time forward speed based on the shaking completion signal. The number of swaying cycles, the initial frequency of swaying, the initial amplitude of torque, and the effective displacement of the body are analyzed to determine the robot's walking parameters.

5. The method for synchronous speed regulation of multiple motors in a robot walking module according to claim 4, characterized in that, The steps to determine the effective displacement of the machine body by analyzing the number of swaying cycles, the initial swaying time, the initial swaying frequency, and the real-time forward velocity include: Calculate the quotient of the number of swaying cycles and the initial swaying frequency to generate the body swaying time; Calculate the sum of the initial shaking time and the shaking time of the machine body to generate the shaking completion time; The real-time forward velocity is integrated based on the initial time and completion time of the swaying to generate the effective displacement of the machine.

6. The method for synchronous speed regulation of multiple motors in a robot walking module according to claim 4, characterized in that, The steps to determine the robot's walking parameters by analyzing the number of swaying cycles, the initial swaying frequency, the initial torque amplitude, and the effective displacement of the body include: Determine whether the effective displacement of the body is greater than the preset effective displacement threshold; If it is greater than the preset normal walking parameters, then the preset normal walking parameters will be defined as the robot walking parameters. If it is not greater than, then obtain the torque limit range; The number of swaying cycles, torque limit amplitude, initial swaying frequency, and initial torque amplitude are analyzed to determine the robot's walking parameters.

7. The method for synchronous speed regulation of multiple motors in a robot walking module according to claim 6, characterized in that, The steps to determine the robot's walking parameters by analyzing the number of swaying cycles, torque limit amplitude, initial swaying frequency, and initial torque amplitude include: Calculate the sum of the initial shaking frequency and the preset shaking frequency increment to generate the final shaking frequency; Calculate the sum of the initial torque magnitude and the preset torque magnitude increment to generate the torque adjustment magnitude; The torque adjustment range and torque limit range are sorted to determine the minimum torque range, and the minimum torque range is defined as the final torque range; The robot's walking parameters are generated by associating the number of swaying cycles, the final torque amplitude, the final swaying frequency, and preset general walking parameters.

8. A multi-motor synchronous speed control system for a robot walking module, characterized in that, include: The acquisition module is used to acquire robot physical parameters, real-time wheel angular velocity, real-time forward speed, and robot walking detection results. A memory for storing a program for a multi-motor synchronous speed control method for a robot walking module as described in any one of claims 1 to 7; The processor and the program in the memory can be loaded and executed by the processor to implement the multi-motor synchronous speed control method for a robot walking module as described in any one of claims 1 to 7.

9. A smart terminal, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as described in any one of claims 1 to 7, which is a method for synchronous speed regulation of multiple motors in a robot walking module.

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