Robotic control method, system, and related devices based on multi-order derivative tracker

Abstract

This application relates to the field of robot control technology, and discloses a robot control method, system, and related equipment based on a multi-order differential tracker. The method includes: acquiring discrete trajectory points through a controller according to a preset control cycle; determining step points by reading the flag bits of the discrete trajectory points; calculating velocity and acceleration based on adjacent discrete trajectory points for non-step points; updating the discrete trajectory points by limiting the velocity or acceleration when it exceeds limits; initial tracking of the target position by a position differential tracker based on the discrete trajectory points; correction of the error between the target position and the robot's current position acquired by the controller by an error differential tracker, and outputting a control trajectory; merging the target position tracking output and the error tracking output to complete aliasing when a step point or error exceeds a threshold; and smoothing the generated control trajectory by a moving average filter. This method improves the robot's motion control accuracy, response speed, and system robustness, can predict the target trajectory with low trajectory lag, and generates a smooth trajectory.

Description

Technical Field

[0001] This application relates to the field of robot control technology, and in particular to a robot control method, system and related equipment based on a multi-order differential tracker. Background Technology

[0002] With the continuous development of robotics technology, especially in the field of robot motion control, the planning and precise control of robot motion trajectories have become one of the key issues for improving robot performance. Traditional robot control methods rely on discrete trajectory points, and the control system performs motion control by gradually tracking these trajectory points. However, traditional technologies often encounter problems when there is a time-domain mismatch between low-frequency discrete inputs and high-frequency real-time control. Traditional systems typically require the trajectory point transmission period to be consistent with the control period, but when the input signal update frequency is lower than the controller processing frequency, the control system struggles to perform precise control effectively, leading to the accumulation of tracking errors and affecting overall performance. With the introduction of reinforcement learning (RL) technology, research in the field of robot control is gradually shifting towards autonomous learning and adaptive control. In practical engineering applications, reinforcement learning strategies typically output discrete trajectory points or discrete action sequences, and their update frequency is often lower than the control frequency of the underlying servo control loop. To enable robots to perform motion at higher control frequencies, existing solutions typically adopt a technical approach of "reinforcement learning predicting discrete trajectory points at several future moments, and then generating continuous trajectories and performing trajectory following through polynomial fitting / spline interpolation, etc." However, this type of processing link, which "predicts discrete points first and then fits a continuous trajectory," is prone to introducing phase lag and following delay when the transmission period is longer than the control period (i.e., there is a time-domain mismatch). The controller's updates to the latest target are not timely enough, leading to error accumulation, slower system response, and consequently affecting control accuracy and stability. This lag effect is particularly pronounced when the target trajectory undergoes a step change or has a large error, easily causing overshoot, oscillation, or prolonged recovery time. On the other hand, some existing technologies still tend to use a single tracking differentiator to compensate for errors. However, their compensation link and dynamic adjustment capabilities are limited, making it difficult to simultaneously achieve both speed and robustness in complex scenarios such as low-frequency discrete trajectory inputs, time-domain mismatch, and step / large errors. Therefore, traditional technologies have significant limitations in handling complex problems such as low-frequency discrete inputs, large errors, and step trajectories. Especially when facing the challenges posed by adaptive control strategies and dynamic environments, control accuracy is difficult to guarantee, response speed is slow, and system robustness is insufficient. Summary of the Invention

[0003] The main technical problem addressed by the embodiments of this application is the insufficient control accuracy, response speed, and system robustness of traditional robot motion control in complex scenarios.

[0004] To solve the above-mentioned technical problems, the first technical solution adopted in the embodiments of this application is: providing a robot control method based on a multi-order differential tracker, comprising: acquiring discrete trajectory points through the robot's controller according to a preset control cycle, wherein the update cycle of the discrete trajectory points is greater than or equal to the preset control cycle; determining whether the current discrete trajectory point is a step point based on the flag bits contained in the discrete trajectory point; if it is not a step point, constraining the discrete trajectory points whose speed and acceleration exceed the limits, limiting the speed and acceleration to within a preset maximum value range; and using the position differential tracker in the preset multi-order differential tracker... Initial tracking of the target position is performed based on the discrete trajectory points; the error differential tracker in the multi-order differential tracker corrects and adjusts the target position based on the error between the target position and the robot's current position obtained by the controller, resulting in a generated control trajectory for robot trajectory control; when the current discrete trajectory point is a step point, or the error between the target position and the robot's current position is greater than a preset threshold, aliasing processing is performed on the generated control trajectory; the generated control trajectory is then filtered, including using a moving average filter to filter the generated control trajectory.

[0005] Optionally, the step of constraining the discrete trajectory points whose speed and acceleration exceed the limits, and limiting the speed and acceleration to within a preset maximum value range, includes: calculating the trajectory speed based on the displacement difference between adjacent discrete trajectory points and the update cycle of the discrete trajectory points; calculating the trajectory acceleration based on the difference between the trajectory speed corresponding to the current update cycle and the trajectory speed corresponding to the previous update cycle, and in conjunction with the update cycle of the discrete trajectory points; and when the trajectory speed or the trajectory acceleration exceeds the preset maximum value range, performing a limiting update on the discrete trajectory points to limit the updated trajectory speed and trajectory acceleration to within the preset maximum value range.

[0006] Optionally, the step of initially tracking the target position using the position differential tracker in a preset multi-order differential tracker, based on the discrete trajectory points, includes: inputting the discrete trajectory points to the position differential tracker; updating the target position tracking value based on the target position tracking value, target velocity tracking value output by the position differential tracker in the previous preset control cycle, and the preset control cycle; updating the target velocity tracking value based on the error between the discrete trajectory points and the updated target position tracking value, a preset maximum acceleration parameter, and a filtering parameter; and outputting the updated target position tracking value as the target position.

[0007] Optionally, the step of correcting and adjusting the target position based on the error between the target position and the current position of the robot obtained by the controller, using the error differential tracker in the multi-order differential tracker to obtain a generated control trajectory for robot trajectory control, includes: performing a difference calculation between the target position and the current position of the robot obtained by the controller to obtain a position error; inputting the position error to the error differential tracker, and correcting the target position based on the error tracking value and error change rate output by the error differential tracker; and setting the corrected target position as the trajectory point output of the generated control trajectory.

[0008] Optionally, the step of performing aliasing processing on the generated control trajectory when the current discrete trajectory point is a step point, or the error between the target position and the robot's current position is greater than a preset threshold, includes: acquiring the target position tracking output output by the position differential tracker and the error tracking output output by the error differential tracker; determining an aliasing coefficient based on whether the current discrete trajectory point is a step point and the comparison result between the error and the preset threshold; and fusing the target position tracking output and the error tracking output based on the aliasing coefficient to obtain the aliased generated control trajectory.

[0009] Optionally, the differential tracker in the position differential tracker and the error differential tracker is implemented using a nonlinear differential tracker, the calculation of which includes: according to Update the position tracking output, where, This indicates the position tracking output. This indicates the target position tracking output from the previous moment. This indicates the preset control period. This represents the target velocity tracking value / velocity state quantity output by the nonlinear differential tracker in the previous control cycle; according to Calculate tracking error , Indicates the current time The input trajectory points; based on Update speed tracking output , This represents the maximum tracking acceleration parameter. Represents the filter parameters; where, , , , , , , This represents the maximum tracking acceleration parameter.

[0010] Optionally, the step of aliasing the generated control trajectory includes: according to Calculate the first An aliasing coefficient is set for a preset control cycle. During aliasing processing, this coefficient adjusts the weight of the error differential tracking term in generating the control trajectory and correspondingly adjusts the fusion ratio between the target position tracking term and the error tracking term. Indicates the error limit. No. i Within each control cycle, the error between the target position input corresponding to the discrete trajectory point and the target position tracking value output by the position differential tracker; according to An error coefficient is calculated, which, when a step point is detected or the error exceeds a higher threshold, scales and suppresses the aliasing contribution of the error term. Indicates the step trajectory generation flag; based on the aliasing coefficient and the error coefficient Update the target position tracking output; for the output of each error differential tracker, according to... A weighted update is performed, and the aliased target position tracking output is set as the generated control trajectory.

[0011] To solve the above-mentioned technical problems, the second technical solution adopted in this application is: providing a robot control device based on a multi-order differential tracker, comprising: a discrete trajectory point acquisition module, used to acquire discrete trajectory points through the robot's controller according to a preset control cycle, wherein the update cycle of the discrete trajectory points is greater than or equal to the preset control cycle; a discrete trajectory point judgment module, used to determine whether the current discrete trajectory point is a step point based on the flag bits contained in the discrete trajectory point, and if it is not a step point, to perform constraint processing on the discrete trajectory point whose speed and acceleration exceed the limits, limiting the speed and acceleration to within a preset maximum value range; and a position differential tracker module, used to use the position differential tracker in the preset multi-order differential tracker... The target position is initially tracked based on the discrete trajectory points; the error differential tracker module is used to correct and adjust the target position based on the error between the target position and the robot's current position obtained by the controller through the error differential tracker in the multi-order differential tracker, to obtain a generated control trajectory for robot trajectory control; the step point aliasing processing module is used to perform aliasing processing on the generated control trajectory when the current discrete trajectory point is a step point, or when the error between the target position and the robot's current position is greater than a preset threshold; the generated trajectory filtering processing module is used to filter the generated control trajectory, the filtering processing including filtering the generated control trajectory using a moving average filter.

[0012] To solve the above-mentioned technical problems, the third technical solution adopted in the embodiments of this application is: to provide an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the robot control method based on the multi-order differential tracker as described above.

[0013] To solve the above-mentioned technical problems, the fourth technical solution adopted in the embodiments of this application is: to provide a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by an electronic device, the electronic device executes the robot control method based on a multi-order differential tracker as described above.

[0014] Unlike related technologies, the position differential tracker in this application performs initial tracking of the target position based on discrete trajectory points, enabling the low-frequency discrete input to form a continuous and recursive target position reference on the control cycle scale. The error differential tracker further corrects the target position based on the error between the target position and the robot's current position, forming a recursive compensation channel for tracking deviations, thereby reducing the tracking lag that is easily generated by a single tracking structure. Simultaneously, when the discrete trajectory point is a step point or the error exceeds a threshold, the generated control trajectory undergoes aliasing processing. By fusing the target position tracking output and the error tracking output, the correction contribution is dynamically adjusted to suppress overshoot and oscillation under step conditions and improve the speed of sudden change following. Therefore, this application achieves faster response and more stable trajectory output in complex trajectories, especially in step and large error scenarios. Attached Figure Description

[0015] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements having the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0016] Figure 1 This is a schematic diagram of the execution flow of the robot control method based on a multi-order differential tracker provided in the embodiments of this application.

[0017] Figure 2 This is a schematic diagram of the trajectory prediction and tracking process based on a multi-order differential tracker provided in the embodiments of this application.

[0018] Figure 3 This is a comparison chart of the overall performance of trajectory prediction and tracking provided in the embodiments of this application.

[0019] Figure 4This is a magnified comparison image of the trajectory prediction and tracking provided in the embodiments of this application.

[0020] Figure 5 This is a magnified comparison image of a step trajectory segment provided in an embodiment of this application.

[0021] Figure 6 This is a schematic diagram of the tracking acceleration curve provided in the embodiments of this application.

[0022] Figure 7 This is a schematic diagram of the acceleration curve tracked by the first-order differential tracker provided in the embodiments of this application.

[0023] Figure 8 This is a schematic diagram of the tracking acceleration curve provided in the embodiments of this application.

[0024] Figure 9 This is a schematic diagram of the velocity curve tracked by the first-order differential tracker provided in the embodiments of this application.

[0025] Figure 10 This is a schematic diagram of the system structure of a robot control device based on a multi-order differential tracker provided in an embodiment of this application.

[0026] Figure 11 This is a schematic diagram of the hardware structure of an electronic device that executes a robot control method based on a multi-order differential tracker, as provided in an embodiment of this application. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. Software tools, components, or servers not belonging to this company that appear in the embodiments of this application are merely illustrative examples and do not represent actual use.

[0028] It should be noted that, unless otherwise specified, the various features in the embodiments of this application can be combined with each other, all of which are within the protection scope of this application. Furthermore, although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device schematic diagram or the order in the flowchart.

[0029] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The term "and / or" as used in this specification includes any and all combinations of one or more of the associated listed items.

[0030] To facilitate understanding of this embodiment, a robot control method based on a multi-order differential tracker disclosed in this application will first be described in detail. Please refer to [link to relevant documentation]. Figure 1 , Figure 1 This is a schematic diagram of the execution flow of the robot control method based on a multi-order differential tracker provided in the embodiments of this application, as shown below. Figure 1 As shown, it includes the following steps: S1. The robot's controller acquires discrete trajectory points according to a preset control cycle, and the update cycle of the discrete trajectory points is greater than or equal to the preset control cycle.

[0031] The purpose of step S1 is to unify the time scale difference between the "target path output by the trajectory planning side" and the "real-time closed-loop control by the controller side": the controller runs closed-loop control with a preset control cycle, but trajectory planning or upper-level tasks usually output discrete trajectory points at a lower frequency. Therefore, the update cycle of discrete trajectory points is set to be greater than or equal to the control cycle, so that the controller can maintain continuous calculation and output in multiple control cycles when the trajectory points are not updated. In each control cycle, the controller reads the currently available discrete trajectory points as the input of the desired target position, and combines them with the processing of step points, velocity / acceleration constraints and multi-order differential tracker tracking prediction in subsequent steps to achieve smoothing of low-frequency discrete input, controllable transition of trajectory changes, and stable input for subsequent error correction and aliasing fusion, thereby laying a unified time reference and data input foundation for generating continuous control trajectories.

[0032] S2. Determine whether the current discrete trajectory point is a step point based on the flag bits contained in the discrete trajectory point. If it is not a step point, then constrain the discrete trajectory points whose speed and acceleration exceed the limits, and limit the speed and acceleration to within the preset maximum value range.

[0033] Step S2 ensures that the robot can effectively control and limit discrete trajectory points when tracking the target trajectory, especially for trajectory points where speed and acceleration may exceed limits. Based on the flag bits in the discrete trajectory points, it is first determined whether the trajectory point is a step point, i.e., whether there is a drastic change. In the case of non-step points, the trajectory point may cause the control system to be unable to handle the problem due to excessive or rapid changes in the target path, resulting in speed or acceleration exceeding limits. To avoid the controller failing to respond in time or the execution process being unstable, these trajectory points are constrained. Through amplitude limiting operations, the speed and acceleration are limited to the set maximum value range, thereby maintaining the smooth operation of the system and the accuracy of trajectory control.

[0034] As an optional implementation, the process of constraining discrete trajectory points with excessive velocity and acceleration in step S2 above may also include the following steps S21 to S23.

[0035] S21. Calculate the trajectory velocity based on the displacement difference between adjacent discrete trajectory points and the update cycle of the discrete trajectory points.

[0036] Trajectory velocity calculation is based on the displacement difference between adjacent discrete trajectory points and the trajectory point update cycle. By calculating the position changes of adjacent trajectory points and the time interval, the system can obtain the velocity information within each control cycle, i.e., the velocity the robot should have at the current moment. This calculation provides the basis for subsequent acceleration calculations, ensuring the accuracy of velocity changes and the smoothness of control within each control cycle.

[0037] S22. Calculate the trajectory acceleration based on the difference between the trajectory velocity corresponding to the current update cycle and the trajectory velocity corresponding to the previous update cycle, and in conjunction with the update cycle of the discrete trajectory points.

[0038] The calculation of trajectory acceleration is based on the difference in trajectory velocity between two consecutive control cycles. Specifically, the difference between the trajectory velocity in the current control cycle and the velocity in the previous cycle is first calculated. Then, combined with the update cycle (i.e., the time interval) of the discrete trajectory points, the trajectory acceleration can be obtained. Acceleration is a measure of the rate of change of velocity, ensuring that the system can consider acceleration limits when the velocity changes, thereby avoiding control instability or damage to the mechanical system caused by excessively rapid velocity changes.

[0039] S23. When the trajectory velocity or trajectory acceleration exceeds the preset maximum value range, the discrete trajectory points are updated with a limiting function to restrict the updated trajectory velocity and trajectory acceleration to the preset maximum value range.

[0040] After calculating the velocity and acceleration, a limiting update is used to ensure that the system's response does not exceed physical limits, leading to unstable control. This step limits the calculated velocity and acceleration values ​​to within a preset maximum range. The aim is to ensure that regardless of how much the trajectory changes, the control system can always adjust the robot's movements within a controllable and stable range, thereby improving overall control accuracy and preventing damage to the mechanical system from exceeding safe limits.

[0041] As a preferred implementation, when performing velocity and acceleration constraint processing on non-step discrete trajectory points, the velocity and acceleration limits of the discrete trajectory points can be updated according to the transmission period. Specifically, this may include: updating the velocity and acceleration limits of the discrete trajectory points received by the controller based on the current data. Discrete trajectory points from the previous transmission cycle Calculate trajectory velocity ,in ;when At that time, the trajectory points after speed limiting Updated to ,when At that time, update the trajectory points after speed limiting to ,when At that time, take Trajectory points based on speed limiting Calculate correction speed ,in And calculate the correction speed corresponding to the previous transmission cycle. ,in ; Calculate trajectory acceleration based on corrected velocity from adjacent transmission cycles ,in ;when At that time, update the trajectory points after acceleration limiting to ,when At that time, update the trajectory points after acceleration limiting to ,when At that time, take ; and will These are discrete trajectory points used for subsequent trajectory prediction and tracking. When no new discrete trajectory points are received at the current time, the trajectory point with acceleration limiting calculated at the most recent time is used. As input to the discrete trajectory points. j This refers to the frame number at the current moment in the transmission cycle; These are the discrete trajectory points received by the controller at the current moment; These are the discrete trajectory points from the previous transmission cycle; These are the discrete trajectory points from the previous two transmission cycles; The control cycle sent by the host computer; For the transmission period; For the reason and The calculated trajectory velocity; The preset maximum speed threshold; These are the discrete trajectory points after speed limiting; For based on The calculated correction rate; This is the correction speed corresponding to the previous transmission cycle; Correct the trajectory acceleration corresponding to the speed difference between adjacent transmission cycles; The preset maximum acceleration threshold; These are the discrete trajectory points after acceleration limiting; i To control the frame number of the current moment in the control cycle; This is the input of discrete trajectory points for subsequent trajectory prediction and tracking.

[0042] Through the above steps S21 to S23, the trajectory velocity and trajectory acceleration calculated based on adjacent discrete trajectory points can be used to determine whether the dynamic changes of discrete trajectory points exceed the preset maximum value range. When the limit is exceeded, the discrete trajectory points are updated with a limiting effect, so that the velocity and acceleration corresponding to the updated discrete trajectory points are controlled, thereby suppressing the velocity jump and acceleration impact caused by the sudden change of discrete trajectory points, reducing the input fluctuation of subsequent tracking and correction links, and improving the executability and stability of generating control trajectories.

[0043] S3. The position of the target is initially tracked based on the discrete trajectory points by the position differential tracker in the preset multi-order differential tracker.

[0044] The purpose of step S3 is to convert the "low-frequency, discrete, and potentially discontinuous" trajectory point input into a target position sequence that can be directly used by the control side and is continuously updated with the control cycle. The position differential tracker plays the role of "first-layer tracking" in the multi-order differential tracker system. Its main function is to perform initial tracking and smoothing recursion on the target position represented by the discrete trajectory points, ensuring the target position has continuity and predictability on the control cycle scale. This also provides a stable reference input for the subsequent error differential tracker, thereby reducing the jitter, hysteresis, and abrupt change sensitivity caused by discrete inputs.

[0045] As an optional implementation, the execution process of step S3 may also include the following steps S31 to S33.

[0046] S31. Input discrete trajectory points to the position differential tracker, and update the target position tracking value based on the target position tracking value, target velocity tracking value and preset control cycle output by the position differential tracker in the previous preset control cycle.

[0047] Step S3 utilizes the historical state of the position differential tracker to achieve recursive updates. That is, the target position tracking value and target velocity tracking value of the previous control cycle are used as the state basis. In the current control cycle, time advances and the state is updated according to the control cycle. This allows the target position tracking value to continue to evolve even if there are no new trajectory points, and to maintain the same tracking direction as the discrete trajectory point input.

[0048] S32. Update the target velocity tracking value based on the error between the discrete trajectory point and the updated target position tracking value, the preset maximum acceleration parameter, and the filtering parameter.

[0049] Step S32 transforms the "deviation between the discrete trajectory point and the current tracking position" into an adjustment amount for the target velocity tracking value, and introduces the maximum acceleration parameter and filtering parameter during the adjustment process to constrain the rate of velocity change and the smoothness of the response. In this way, the update of the target velocity tracking value can reflect the tracking requirements brought about by the change of trajectory points, without excessively rapid velocity jumps or high-frequency jitter, providing controlled dynamic characteristics for the subsequent generation of control trajectories.

[0050] S33. Output the updated target position tracking value as the target position.

[0051] Through steps S31 to S33, the position differential tracker transforms discrete trajectory points into target position outputs that are continuously updated on the control cycle scale. By recursively updating the target velocity tracking value, the tracking response is adjusted under the constraints of preset maximum acceleration parameters and filtering parameters, so that the target position output has better continuity and smoothness relative to the discrete trajectory points. This provides a stable target position reference for subsequent correction based on the current position error and reduces tracking lag.

[0052] S4. The error differential tracker in the multi-order differential tracker corrects and adjusts the error between the target position and the robot's current position obtained by the controller to obtain the generated control trajectory for robot trajectory control.

[0053] The purpose of step S4 is to further integrate the target position output by the position differential tracker with the robot's actual motion state in a closed loop, so that the generated control trajectory can reflect real-time tracking deviations and be dynamically corrected. The error differential tracker plays the role of "error layer tracking" in the multi-order differential tracker system. Its input is the error between the target position and the robot's current position. By tracking the error and its changing trend, it forms a correction amount for the target position. This ensures that the generated control trajectory not only inherits the instruction intent of the target trajectory but also compensates for deviations caused by lag, disturbances, and model uncertainties during execution, providing a more realistic and executable sequence of trajectory points for subsequent aliasing and filtering processes.

[0054] As an optional implementation, the execution process of step S4 above may further include the following steps S41 to S43.

[0055] S41. Perform a difference calculation between the target position and the robot's current position obtained by the controller to obtain the position error.

[0056] Step S41 constructs an error signal for the error differential tracker to process within the current control cycle. That is, the deviation between the "desired state and the actual state" is explicitly quantified into a position error by the difference between the target position and the robot's current position. This error is used as the input reference for subsequent error tracking and correction calculations, so that error processing and trajectory generation are aligned on the same control cycle scale.

[0057] S42. Input the position error to the error differential tracker, and correct the target position based on the error tracking value and error change rate output by the error differential tracker.

[0058] Step S42 inputs the position error into the error differential tracker, causing the error differential tracker to output the error tracking value and the error change rate, and thereby form a correction amount for the target position; wherein, the error tracking value is used to characterize the smooth estimation of the error, and the error change rate is used to characterize the changing trend of the error. Both are used together to drive the dynamic adjustment of the target position, so that the correction process can respond to the error change and avoid the high-frequency fluctuations caused by directly using the original error.

[0059] S43. Set the corrected target position as the trajectory point output for generating the control trajectory.

[0060] In a preferred embodiment, the differential tracker in the above-mentioned position differential tracker and error differential tracker is implemented using a nonlinear differential tracker. The calculation of the nonlinear differential tracker includes: according to Update the position tracking output, where, This indicates the position tracking output. This indicates the target position tracking output from the previous moment. Indicates the preset control cycle. This represents the target velocity tracking value / velocity state quantity output by the nonlinear differential tracker in the previous control cycle; according to Calculate tracking error , Indicates the current time The input trajectory points; based on Update speed tracking output , This represents the maximum tracking acceleration parameter. Represents the filter parameters; where, , , , , , , This represents the maximum tracking acceleration parameter.

[0061] As an example, please refer to Figure 2 , Figure 2This is a schematic diagram of the trajectory prediction and tracking process based on a multi-order differential tracker provided in an embodiment of this application, as shown below. Figure 2 As shown, input trajectory First, the system enters the trajectory preprocessing module to obtain the input quantities used for subsequent tracking calculations. This input quantity The data is fed into a multi-stage differential tracker module, where the initial tracking output from the position layer and the recursive compensation output from the error layer together form a cascaded tracking link. Specifically, the first-stage differential tracker... Initial tracking was performed to obtain and based on The difference forms an error This error is used as the input to the subsequent differential tracker; the second-stage differential tracker processes the error... Track and with Superimposed and further by and The difference forms an error For use by higher-order differential trackers; the third-level differential tracker for error... Track and with Superimposed This allows for recursive predictive tracking output of the input trajectory. When the tracking error is at a preset large error condition, the output of the multi-order differential tracker enters the "differential tracker aliasing when the tracking error is large" module. Based on the error state, the position layer output and the error layer output are fused and adjusted to obtain the aliased trajectory output. Subsequently, the aliased trajectory output enters the filtering module for smoothing, and finally, the trajectory is output. As a result of trajectory prediction and tracking. , , , , ,in, , , These represent the first differential tracker operator, the second differential tracker operator, and the third differential tracker operator, respectively.

[0062] Through steps S41 to S43 above, the difference between the target position and the robot's current position is quantified as a position error and input into the error differential tracker. The error tracking value and error change rate output by the error differential tracker are used to recursively correct the target position, so that the generated control trajectory can compensate for the tracking deviation in real time with the control cycle and suppress the influence of error fluctuation on the output trajectory, thereby reducing tracking lag and improving the stability of trajectory control.

[0063] S5. When the current discrete trajectory point is a step point or the error between the target position and the current position of the robot is greater than a preset threshold, perform aliasing processing on the generated control trajectory.

[0064] Among them, the goal of step S5 is to dynamically correct and fuse the generated control trajectory during the control process. Especially when encountering a step point or the error exceeding the set threshold, it ensures that the response of the control system can quickly follow the trajectory change and avoid over-control or instability. The aliasing processing performs weighted fusion on the target position tracking output and the error differential tracking output, enabling the system to flexibly adjust the trajectory output under different control scenarios, ensuring the smoothness and accuracy of the trajectory, and avoiding control shocks caused by mutations or large errors. Through this step, the system can perform adaptive correction for complex and mutated trajectory changes or errors, further enhancing the robustness and response performance of the robot trajectory control.

[0065] As an optional implementation manner, the execution process of the above step S5 may further include the following steps S51 to S53.

[0066] S51. Obtain the target position tracking output output by the position differential tracker and the error tracking output output by the error differential tracker.

[0067] First, obtain two important output signals from the position differential tracker and the error differential tracker: the target position tracking output and the error tracking output. The target position tracking output comes from the position differential tracker and represents the target position that the robot should reach within the current control cycle; the error tracking output comes from the error differential tracker and represents the deviation between the current position and the target position of the robot. By obtaining these two signals simultaneously, the difference between the current position and the target position can be comprehensively evaluated, providing the necessary basic data for subsequent aliasing processing. This process provides input information for aliasing processing, enabling the system to make further adjustments by combining the target position and error information.

[0068] S52. Determine the aliasing coefficient according to whether the current discrete trajectory point is a step point and the comparison result between the error and the preset threshold.

[0069] Among them, if the current trajectory point is a step point, it means that the target position has changed greatly, and the system needs to increase the correction strength for the error. If the error is greater than the set threshold, it means that the current tracking accuracy is poor, and the system also needs to enhance the correction of the error. In this way, the system can dynamically adjust the aliasing coefficient according to the actual situation of the trajectory change, ensuring that the control system can make timely responses in the case of large trajectory changes or large errors, so as to prevent overcorrection or slow reaction.

[0070] S53. Based on the aliasing coefficient, the target position tracking output and the error tracking output are fused to obtain the generated control trajectory after aliasing.

[0071] The system employs a weighted fusion process, combining the calculated aliasing coefficient with the target position tracking output and error tracking output, to obtain the aliased generated control trajectory. The aliasing coefficient determines the fusion ratio of the target position output and error output in the final trajectory, thereby adjusting the smoothness and responsiveness of the control trajectory. Through this fusion process, the system can balance the influence of target position and error correction based on the current trajectory conditions, ensuring that the robot can stably and accurately follow the target trajectory and effectively address control challenges caused by trajectory changes or error fluctuations.

[0072] As a preferred embodiment, the above-described step of aliasing the generated control trajectory includes: according to Calculate the first The aliasing coefficient is set for a preset control cycle. During aliasing processing, the aliasing coefficient adjusts the weight of the error differential tracking term in generating the control trajectory, and correspondingly adjusts the fusion ratio between the target position tracking term and the error tracking term. Indicates the error limit. No. i Within each control cycle, the error between the target position input corresponding to the discrete trajectory point and the target position tracking value output by the position differential tracker; according to The error coefficient is calculated, and when a step point is detected or the error exceeds a higher threshold, the aliasing contribution of the error term is scaled and suppressed. Indicates the generation of step trajectory; based on aliasing coefficient and error coefficient Update the target position tracking output; for the output of each error differential tracker, according to... Perform a weighted update and set the aliased target position tracking output as the generated control trajectory.

[0073] As an example, when performing aliasing on the generated control trajectory, the tracking error can be adjusted if a preset condition is met (e.g., the error exceeds the error limit). Or a step trajectory marker was detected. In this case, the participation weights of the outputs of each stage of the multi-order differential tracker are dynamically adjusted to achieve the fusion update of the position layer output and the error layer output. Based on the output of the previous control cycle, the outputs of each stage of the multi-order differential tracker are fused and updated. The position layer (first differential tracker) output is supplemented with a weighted superposition of the error layer (second and third differential trackers) outputs. For example, the previous cycle output of the first differential tracker is updated as follows: The error layer output is then updated by attenuation based on the aliasing coefficient, for example: , This allows the position layer output to synchronize with the error layer output when the error is large or when a step condition is triggered. and The determined weight relationships are fused to obtain the aliased trajectory output for subsequent control. Among these, Indicates the first The output of the first differential tracker during each control cycle; Indicates the first The output of the second differential tracker during each control cycle; Indicates the first The output of the third differential tracker during each control cycle.

[0074] Please continue reading. Figure 3 , Figure 3 This is a comparison chart of the overall performance of trajectory prediction and tracking using the multi-order differential tracker provided in this application embodiment. The blue curve represents the input discrete trajectory points, the orange curve represents the tracking output obtained using a single differential tracker, and the red curve represents the tracking output obtained using a multi-order differential tracker. In this embodiment, the parameters of the single differential tracker are set as follows: , The multi-order differential tracker, taking a third-order differential tracker as an example, has the parameters of the first-order differential tracker set as follows: 0、 The parameters of the second-order differential tracker are set as follows: , The parameters of the third-order differential tracker are set as follows: , Furthermore, in this embodiment, the maximum acceleration used for limitation is set to 800. For example... Figure 3 As shown, the input trajectory contains two different types of trajectories: the first segment is a low-frequency trajectory signal, and the second segment is a high-frequency trajectory signal. Under this combined input, the output of the multi-order differential tracker maintains a high degree of consistency with the original trajectory points and can achieve good tracking output in different frequency bands.

[0075] Please continue reading. Figure 4 , Figure 4 This is a magnified comparison image of a portion of the trajectory prediction and tracking provided in an embodiment of this application. For example... Figure 4 As shown, within the local continuous variation range, the output of the multi-order differential tracker has a smaller tracking lag trend compared to the output of a single differential tracker. The output curve follows the original trajectory point more closely and has a higher degree of fit within the local interval, thus demonstrating the tracking consistency advantage of the multi-order differential tracker in the continuous variation segment.

[0076] Please continue reading. Figure 5 , Figure 5 This is a magnified comparison image of a partial step trajectory segment provided in an embodiment of this application. For example... Figure 5 As shown, within the range where the input trajectory exhibits a step change, the multi-order differential tracker output maintains a relatively smooth transition process before and after the step, with a relatively reduced overshoot and oscillation amplitude during the step response process. Furthermore, under the constraint of a maximum acceleration limit of 800°, the trajectory output change process remains within the corresponding limit range. Meanwhile, from the local magnified comparison, it can be seen that the multi-order differential tracker exhibits a small lag in the trajectory following process during the step segment and shows a certain feedforward prediction trend, which is more obvious in the tracking of low-frequency trajectory segments.

[0077] S6. Filter the generated control trajectory. The filtering process includes using a moving average filter to filter the generated control trajectory.

[0078] Step S6 further smooths the generated control trajectory output from the preceding steps to suppress high-frequency fluctuations that may be introduced during discrete sampling, error correction, and aliasing fusion, making the output trajectory more continuous and stable on the control cycle scale. Specifically, a moving average filter is applied to the generated control trajectory, and the mean of the trajectory points is calculated within a preset sliding window. The mean result is then used to update the corresponding trajectory points, thereby reducing the abrupt changes and jitter of trajectory points in adjacent control cycles while maintaining the overall trend of the trajectory. This makes the final output control trajectory more suitable as an input sequence for robot trajectory control and improves the smoothness of subsequent execution.

[0079] Please continue reading. Figure 6 , Figure 6 This is a schematic diagram of the tracking acceleration curve provided in an embodiment of this application. Figure 6 As shown, after completing multi-order differential tracking and performing filtering on the generated control trajectory, the acceleration dimension of the output trajectory is characterized. The resulting acceleration curve is used to reflect the dynamic change intensity of the output trajectory in the high-frequency and abrupt change segments. This acceleration curve can intuitively reflect the acceleration fluctuation level of the output trajectory during the control process and is used to verify that the output trajectory meets the preset acceleration limit requirements.

[0080] Please continue reading. Figure 7 , Figure 7 This is a schematic diagram of the acceleration curve tracked by the first-order differential tracker provided in the embodiments of this application. Figure 7 As shown, under the same input trajectory conditions, when only a first-order differential tracker is used for tracking, the acceleration dimension of its tracking output is characterized to obtain the corresponding acceleration curve; this curve is used to compare with... Figure 6The comparison is conducted to reflect the differences in dynamic response and acceleration fluctuation characteristics of different tracking structures under operating conditions such as high frequency and sudden change, thereby providing a reference for the trajectory smoothness and dynamic constraint satisfaction.

[0081] Please continue reading. Figure 8 , Figure 8 This is a schematic diagram of the tracking acceleration curve provided in an embodiment of this application. Figure 8 As shown, the velocity dimension of the generated control trajectory after filtering is characterized to obtain the velocity curve. The velocity curve is used to reflect the continuity of the velocity change of the output trajectory over time, especially to observe whether the velocity fluctuation of the high-frequency trajectory segment is suppressed and whether the output remains continuous and smooth, thus reflecting the contribution of filtering to the smoothness of the trajectory output.

[0082] Please continue reading. Figure 9 , Figure 9 This is a schematic diagram of the velocity curve tracked by the first-order differential tracker provided in the embodiments of this application. Figure 9 As shown, the speed curves output by the comparison scheme are used to... Figure 8 The comparison is made to reflect the differences in the smoothness and fluctuation characteristics of the output velocity changes of different tracking structures under the same input trajectory, providing a reference for evaluating the smoothness and controllability of the output trajectory.

[0083] The robot control method based on a multi-order differential tracker provided in this application introduces velocity and acceleration constraints on the discrete trajectory point input side to limit the variation of discrete trajectory points within a preset maximum range. The discrete trajectory points are initially tracked by a position differential tracker to form a continuous target position reference. The control trajectory is generated by recursively correcting the error between the target position and the robot's current position using an error differential tracker. The generated control trajectory is aliased and fused under step points or when the error exceeds a threshold. At the same time, the generated control trajectory is smoothed by moving average filtering. Thus, faster trajectory following response and reduced overshoot and oscillation are achieved in low-frequency discrete input and step trajectory scenarios. Moreover, a smoother and more stable control trajectory is output while meeting the acceleration limit requirements.

[0084] Please continue reading. Figure 10 , Figure 10 This is a schematic diagram of the system structure of the robot control device based on a multi-order differential tracker provided in the embodiments of this application, as shown below. Figure 10 As shown, the robot control device 50 based on a multi-order differential tracker includes: a discrete trajectory point acquisition module 51, a discrete trajectory point judgment module 52, a position differential tracker module 53, an error differential tracker module 54, a step point aliasing processing module 55, and a generated trajectory filtering processing module 56.

[0085] The discrete trajectory point acquisition module 51 is specifically used to acquire discrete trajectory points through the robot's controller according to a preset control cycle, wherein the update cycle of the discrete trajectory points is greater than or equal to the preset control cycle.

[0086] The discrete trajectory point judgment module 52 is specifically used to determine whether the current discrete trajectory point is a step point based on the flag bit contained in the discrete trajectory point. If it is not a step point, then the discrete trajectory point with excessive speed and acceleration is constrained to limit the speed and acceleration to within the preset maximum value range.

[0087] The position differential tracker module 53 is specifically used to perform initial tracking of the target position based on discrete trajectory points through the position differential tracker in the preset multi-order differential tracker.

[0088] The error differential tracker module 54 is specifically used to correct and adjust the error between the target position and the current position of the robot obtained by the controller through the error differential tracker in the multi-order differential tracker, so as to obtain a generated control trajectory for robot trajectory control.

[0089] The step point aliasing processing module 55 is used to perform aliasing processing on the generated control trajectory when the current discrete trajectory point is a step point, or when the error between the target position and the robot's current position is greater than a preset threshold.

[0090] The generated trajectory filtering module 56 is used to filter the generated control trajectory, and the filtering process includes using a moving average filter to filter the generated control trajectory.

[0091] As an optional implementation, the discrete trajectory point judgment module 52 is further specifically used to calculate the trajectory velocity based on the displacement difference between adjacent discrete trajectory points and the update cycle of the discrete trajectory points; calculate the trajectory acceleration based on the difference between the trajectory velocity corresponding to the current update cycle and the trajectory velocity corresponding to the previous update cycle, and in combination with the update cycle of the discrete trajectory points; when the trajectory velocity or trajectory acceleration exceeds a preset maximum value range, perform amplitude limiting updates on the discrete trajectory points to limit the updated trajectory velocity and trajectory acceleration within the preset maximum value range.

[0092] As an optional implementation, the position differential tracker module 53 is further specifically used to input discrete trajectory points to the position differential tracker, update the target position tracking value based on the target position tracking value, target velocity tracking value, and preset control cycle output by the position differential tracker in the previous preset control cycle; update the target velocity tracking value according to the error between the discrete trajectory point and the updated target position tracking value, the preset maximum acceleration parameter, and the filtering parameter; and output the updated target position tracking value as the target position.

[0093] As an optional implementation, the error differential tracker module 54 is further specifically used to perform a difference calculation between the target position and the robot's current position obtained by the controller to obtain the position error; input the position error to the error differential tracker, and correct the target position based on the error tracking value and error change rate output by the error differential tracker; and set the corrected target position as the trajectory point output for generating the control trajectory.

[0094] As an optional implementation, the step point aliasing processing module 55 is further specifically used to acquire the target position tracking output of the position differential tracker and the error tracking output of the error differential tracker; determine the aliasing coefficient based on whether the current discrete trajectory point is a step point and the comparison result of the error with a preset threshold; and fuse the target position tracking output and the error tracking output based on the aliasing coefficient to obtain the generated control trajectory after aliasing.

[0095] As an optional implementation, the position differential tracker module 53 is further specifically used to... Update the position tracking output, where, This indicates the position tracking output. This indicates the target position tracking output from the previous moment. Indicates the preset control cycle. This represents the target velocity tracking value / velocity state quantity output by the nonlinear differential tracker in the previous control cycle; according to Calculate tracking error , Indicates the current time The input trajectory points; based on Update speed tracking output , This represents the maximum tracking acceleration parameter. Represents the filter parameters; where, , , , , , , This represents the maximum tracking acceleration parameter.

[0096] As an optional implementation, the step point aliasing processing module 55 is further specifically used to... Calculate the first The aliasing coefficient is set for a preset control cycle. During aliasing processing, the aliasing coefficient adjusts the weight of the error differential tracking term in generating the control trajectory, and correspondingly adjusts the fusion ratio between the target position tracking term and the error tracking term. Indicates the error limit. No. iWithin each control cycle, the error between the target position input corresponding to the discrete trajectory point and the target position tracking value output by the position differential tracker; according to The error coefficient is calculated, and when a step point is detected or the error exceeds a higher threshold, the aliasing contribution of the error term is scaled and suppressed. Indicates the generation of step trajectory; based on aliasing coefficient and error coefficient Update the target position tracking output; for the output of each error differential tracker, according to... Perform a weighted update and set the aliased target position tracking output as the generated control trajectory.

[0097] It should be noted that the robot control device based on the multi-order differential tracker described above can execute the robot control method based on the multi-order differential tracker provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects of the method. Technical details not described in detail in the embodiments of the robot control device based on the multi-order differential tracker can be found in the robot control method based on the multi-order differential tracker provided in the embodiments of this application.

[0098] Figure 11 This is a schematic diagram of the hardware structure of an electronic device that executes a robot control method based on a multi-order differential tracker, as provided in an embodiment of this application. Figure 11 As shown, the electronic device 600 includes: One or more processors 610 and memory 620, Figure 11 Take the 610 processor as an example.

[0099] The processor 610 and the memory 620 can be connected via a bus or other means. Figure 11 Taking the example of a connection between China and Israel via a bus.

[0100] The memory 620, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the robot control method based on a multi-order differential tracker in the embodiments of this application. The processor 610 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions, and modules stored in the memory 620, thereby realizing the robot control method based on a multi-order differential tracker in the above-described method embodiments.

[0101] The memory 620 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the robot control device based on the multi-order differential tracker. Furthermore, the memory 620 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 620 may optionally include memory remotely located relative to the processor 610, and these remote memories can be connected to the robot control device based on the multi-order differential tracker via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0102] The one or more modules are stored in the memory 620. When executed by the one or more processors 610, they perform the robot control method based on a multi-order differential tracker in any of the above method embodiments. For example, they perform the above-described... Figure 1 Steps S1 to S6 in the method are implemented. Figure 10 The functions of modules 51-56 in the document.

[0103] The above-described product can perform the methods provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects for performing the methods. Technical details not described in detail in this embodiment can be found in the methods provided in the embodiments of this application.

[0104] This application provides a non-volatile computer-readable storage medium storing computer-executable instructions that are executed by one or more processors, for example... Figure 11 One of the processors 610 enables the one or more processors to execute the robot control method based on a multi-order differential tracker in any of the above method embodiments, for example, to perform the above-described... Figure 1 Steps S1 to S6 in the method are implemented. Figure 10 The functions of modules 51-56 in the document.

[0105] This application provides a computer program product, which includes a computer program stored on a non-volatile computer-readable storage medium. The computer program includes program instructions, which, when executed by an electronic device, enable the electronic device to perform the robot control method based on a multi-order differential tracker in any of the above method embodiments, for example, to perform the above-described... Figure 1 Steps S1 to S6 in the method are implemented. Figure 10 The functions of modules 51-56 in the document.

[0106] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0107] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software and a general-purpose hardware platform, or of course, using hardware. Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and not to limit them; under the concept of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of this application as described above, which are not provided in detail for the sake of brevity; although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A robot control method based on a multi-order differential tracker, characterized in that, include: Discrete trajectory points are acquired by the robot's controller according to a preset control cycle, and the update cycle of the discrete trajectory points is greater than or equal to the preset control cycle. Based on the flag bits contained in the discrete trajectory points, it is determined whether the current discrete trajectory point is a step point. If it is not a step point, then the discrete trajectory points whose speed and acceleration exceed the limits are constrained to limit the speed and acceleration to within the preset maximum value range. The target position is initially tracked based on the discrete trajectory points using the position differential tracker in the preset multi-order differential tracker; The error differential tracker in the multi-order differential tracker corrects and adjusts the error between the target position and the robot's current position obtained by the controller to obtain a generated control trajectory for robot trajectory control. When the current discrete trajectory point is a step point, or the error between the target position and the robot's current position is greater than a preset threshold, the generated control trajectory is subjected to aliasing processing. The generated control trajectory is filtered, and the filtering process includes using a moving average filter to filter the generated control trajectory.

2. The robot control method based on a multi-order differential tracker according to claim 1, characterized in that, The step of constraining the discrete trajectory points whose velocity and acceleration exceed the limits, and restricting the velocity and acceleration to within a preset maximum value range, includes: The trajectory velocity is calculated based on the displacement difference between adjacent discrete trajectory points and the update period of the discrete trajectory points. The trajectory acceleration is calculated based on the difference between the trajectory velocity corresponding to the current update cycle and the trajectory velocity corresponding to the previous update cycle, combined with the update cycle of the discrete trajectory points. When the trajectory velocity or the trajectory acceleration exceeds a preset maximum value range, the discrete trajectory points are updated with a limiting function, and the updated trajectory velocity and trajectory acceleration are limited to the preset maximum value range.

3. The robot control method based on a multi-order differential tracker according to claim 1, characterized in that, The step of initially tracking the target position based on the discrete trajectory points using the position differential tracker in the preset multi-order differential tracker includes: The discrete trajectory points are input to the position differential tracker, and the target position tracking value is updated based on the target position tracking value, target velocity tracking value output by the position differential tracker in the previous preset control cycle and the preset control cycle. The target velocity tracking value is updated based on the error between the discrete trajectory point and the updated target position tracking value, the preset maximum acceleration parameter, and the filtering parameter; The updated target position tracking value is output as the target position.

4. The robot control method based on a multi-order differential tracker according to claim 1, characterized in that, The step of correcting and adjusting the error between the target position and the robot's current position obtained by the controller using the error differential tracker in the multi-order differential tracker to obtain a generated control trajectory for robot trajectory control includes: The position error is obtained by performing a difference calculation between the target position and the robot's current position obtained by the controller; The position error is input to the error differential tracker, and the target position is corrected based on the error tracking value and error change rate output by the error differential tracker. The corrected target position is set as the trajectory point output of the generated control trajectory.

5. The robot control method based on a multi-order differential tracker according to claim 1, characterized in that, When the current discrete trajectory point is a step point, or the error between the target position and the robot's current position is greater than a preset threshold, the step of performing aliasing processing on the generated control trajectory includes: Obtain the target position tracking output from the position differential tracker and the error tracking output from the error differential tracker; The aliasing coefficient is determined based on whether the current discrete trajectory point is a step point and the comparison result between the error and the preset threshold. The target position tracking output and the error tracking output are fused based on the aliasing coefficient to obtain the generated control trajectory after aliasing.

6. The robot control method based on a multi-order differential tracker according to claim 1, characterized in that, The differential tracker in the position differential tracker and the error differential tracker is implemented using a nonlinear differential tracker, and the calculation of the nonlinear differential tracker includes: according to Update the position tracking output, where, This indicates the position tracking output. This indicates the target position tracking output from the previous moment. This indicates the preset control period. This represents the target velocity tracking value / velocity state quantity output by the nonlinear differential tracker in the previous control cycle; according to Calculate tracking error , Indicates the current time The input trajectory points; according to Update speed tracking output , This represents the maximum tracking acceleration parameter. Indicates the filter parameters; in, , , , , , , This represents the maximum tracking acceleration parameter.

7. The robot control method based on a multi-order differential tracker according to claim 1, characterized in that, The step of performing aliasing processing on the generated control trajectory includes: according to Calculate the first An aliasing coefficient is set for a preset control cycle. During aliasing processing, this coefficient adjusts the weight of the error differential tracking term in generating the control trajectory and correspondingly adjusts the fusion ratio between the target position tracking term and the error tracking term. Indicates the error limit. No. i Within each control cycle, the error between the target position input corresponding to the discrete trajectory point and the target position tracking value output by the position differential tracker; according to An error coefficient is calculated, which, when a step point is detected or the error exceeds a higher threshold, scales and suppresses the aliasing contribution of the error term. Indicates the generation of a step trajectory; Based on the aliasing coefficient and the error coefficient Update the target position tracking output; The output of each error differential tracker is according to A weighted update is performed, and the aliased target position tracking output is set as the generated control trajectory.

8. A robot control device based on a multi-order differential tracker, characterized in that, include: The discrete trajectory point acquisition module is used to acquire discrete trajectory points through the robot's controller according to a preset control cycle, wherein the update cycle of the discrete trajectory points is greater than or equal to the preset control cycle. The discrete trajectory point judgment module is used to determine whether the current discrete trajectory point is a step point based on the flag bits contained in the discrete trajectory point. If it is not a step point, the discrete trajectory point whose speed and acceleration exceed the limit is constrained to limit the speed and acceleration to within the preset maximum value range. The position differential tracker module is used to initially track the target position based on the discrete trajectory points using the position differential tracker in the preset multi-order differential tracker. The error differential tracker module is used to correct and adjust the error between the target position and the robot's current position obtained by the controller through the error differential tracker in the multi-order differential tracker, so as to obtain a generated control trajectory for robot trajectory control. The step point aliasing processing module is used to perform aliasing processing on the generated control trajectory when the current discrete trajectory point is a step point, or when the error between the target position and the current position of the robot is greater than a preset threshold. A trajectory filtering module is used to filter the generated control trajectory, wherein the filtering process includes using a moving average filter to filter the generated control trajectory.

9. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed, enables the at least one processor to perform the robot control method based on a multi-order differential tracker as described in any one of claims 1-7.

10. A non-volatile computer-readable storage medium, characterized in that, The non-volatile computer-readable storage medium stores computer-executable instructions, which, when executed by an electronic device, cause the electronic device to perform the robot control method based on a multi-order differential tracker as described in any one of claims 1-7.

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