Robot servo parameter self-adaption method and system based on gravity compensation

Abstract

The invention discloses a robot servo parameter self-adaption method and system based on gravity compensation. The method comprises the steps that before the mechanical arm is installed, instruction debugging is conducted on each joint under different loads, the rotating speed of the joints and the rotating speed of a motor are obtained, control parameters are adjusted and calibrated, and finally the calibration result is stored as joint feature information; modeling a mechanical structure, and calculating dynamic parameters of the mass, the mass center and the motor deflection angle of an arm lever; in the operation process, the load is monitored, and a gravity compensation value is calculated in combination with attitude information; uniformly distributing the compensation value to a control period through a feedforward data channel, and applying the compensation value to a motor and a load as a compensation amount of a torque ring instruction; and the servo system dynamically adjusts the control parameter according to the gravity compensation value and the setting parameter. By implementing the method provided by the embodiment of the invention, the defects in parameter setting and dynamic adaptability of the existing technical scheme can be overcome, and the robustness and performance of the servo system in a variable environment can be improved.

Description

Technical Field

[0001] The invention relates to a servo motor parameter adjustment method, and in particular to a robot servo parameter self-adaptation method and system based on gravity compensation. Background Art

[0002] Servo motor-driven joints are widely used in humanoid robots, industrial robots, and collaborative robots, and are highly valued as drive control mechanisms. In these robots, the servo systems of the joints are strongly coupled, meaning that the movement of one joint directly affects the movement of other joints. Therefore, the interaction between the joints needs to be considered when designing and controlling these servo systems.

[0003] As the robot's posture and load change, the load inertia of the joint will also change. This change places higher demands on the robustness of the servo parameters. Robustness refers to the ability of the servo system to operate stably and effectively in the face of uncertainty and changes. Therefore, it is particularly important to design a control algorithm that can adapt to these changes.

[0004] At present, there are two main methods for servo parameter tuning: single-group parameter tuning and inertia identification-based tuning. The single-group parameter tuning method relies on the experience of the commissioning personnel and uses a set of fixed parameters to cope with a variety of different working conditions. This method often limits the response performance of the servo system when facing a complex and changeable working environment, resulting in reduced efficiency. The inertia identification-based tuning method dynamically adjusts the control parameters according to the identified load inertia during use to improve the performance of the servo system in different states. This method can theoretically give full play to the performance of the servo motor, but there are some limitations in practical applications, such as the need to perform online inertia identification in the host computer or servo system, which has certain requirements for the trajectory and acceleration of the servo operation. Under certain special working conditions, identification failure may occur, affecting the stability and performance of the system. There are also some algorithms that require real-time calculation of the robot dynamics model, which requires accurate understanding of the weight and center of gravity position of the robot load. Faced with random load conditions, these methods lack adaptability, resulting in reduced control accuracy.

[0005] Therefore, it is necessary to design a new method to solve the deficiencies of existing technical solutions in parameter setting and dynamic adaptability, and to improve the robustness and performance of the servo system in a changing environment. Summary of the invention

[0006] The purpose of the present invention is to overcome the defects of the prior art and provide a robot servo parameter self-adaptation method and system based on gravity compensation.

[0007] To achieve the above object, the present invention adopts the following technical solution: a robot servo parameter adaptive method based on gravity compensation, comprising:

[0008] Before installing the robot, send specific instructions to each joint of the robot under different load conditions to obtain the joint load end speed and motor end speed, and adjust and calibrate the control parameters. After obtaining the control effect that meets the requirements, store the calibrated control parameters as joint feature information in the joint internal memory;

[0009] Model and analyze the robot's mechanical structure, and calculate the mechanical structure's mass, center of mass position, and motor shaft deflection angle dynamic parameters;

[0010] During the operation of the robot, the load of the robot is monitored, and the gravity compensation value of each joint is calculated based on the robot's own posture information;

[0011] Each joint receives the gravity compensation value through the feedforward data channel and uses the data interpolation algorithm to evenly distribute it to each control cycle;

[0012] When the robot is working, each joint uses the gravity compensation value as the compensation amount of the torque loop instruction, and applies it to the motor and the load through the torque control loop; and the control parameters of the servo system that drives the movement of the robot arm are dynamically calculated based on the gravity compensation value and the adjusted control parameters.

[0013] The further technical solution is: before the robot is installed, specific instructions are sent to each joint of the robot under different load conditions to obtain the joint load end speed and motor end speed, and the control parameters are adjusted and calibrated at the same time. After obtaining the control effect that meets the requirements, the calibrated control parameters are stored as joint feature information in the joint internal memory, including:

[0014] Before the robot is installed, the response of the joints under different loads is tested, and a set number of control parameters are selected from the test results to obtain calibrated control parameters, which are then stored as joint feature information in the joint's internal memory.

[0015] Its further technical solution is: the calibrated control parameters meet the performance requirements under three different load conditions: large, medium and small.

[0016] The further technical solution is: during the operation of the robot, the load of the robot is monitored, and the gravity compensation value of each joint is calculated in combination with the posture information of the robot itself; each joint uses a feedforward data channel to receive the gravity compensation value, and uses a data interpolation algorithm to subdivide and evenly distribute it to each control cycle, including:

[0017] During the operation of a robot with a robotic arm, monitor the load of the robotic arm;

[0018] The gravity compensation value of each joint is calculated according to the joint gravity compensation torque calculation formula according to the load of the robotic arm. Each joint receives the gravity compensation value through a feedforward data channel and subdivides and evenly distributes it to each control cycle using a data interpolation algorithm.

[0019] A further technical solution is: during the operation of the robot with the mechanical arm, monitoring the load of the mechanical arm comprises:

[0020] During the operation of a robot with a robotic arm, the total gravity of the robotic arm minus the gravity of the robotic arm itself is used to determine the load of the robotic arm.

[0021] Its further technical solution is: the gravity compensation value of each joint is calculated according to the joint gravity compensation torque calculation formula according to the load of the mechanical arm, each joint uses a feedforward data channel to receive the gravity compensation value, and uses a data interpolation algorithm to subdivide and evenly distribute it to each control cycle, including:

[0022] For each joint of the robot arm, τ n =A1·A2·...·A n ·T n ·T n+1 ·G 负载 Calculate the gravity compensation value, where A i Represents the dynamic parameters of the joint, T n Represents the moment arm of the joint, G 负载 Indicates the robot arm load.

[0023] Its further technical solution is: the force arm of the joint is through T n =cosθ·Len, where θ is the joint angle and Len is the length of the corresponding joint.

[0024] The further technical solution is: when the robot is working, each joint uses the gravity compensation value as the compensation amount of the torque loop instruction, and applies it to the motor and the load through the torque control loop; and the control parameters of the servo system that drives the robot arm to move are dynamically calculated according to the gravity compensation value and the adjusted control parameters, including:

[0025] use Calculate the control parameters of the servo system that drives the robot arm, where PI represents the matrix of the speed loop control parameters PI = [P v ,I v ], represents the control parameters of the servo system driving the robot arm, G comp Indicates the gravity compensation value. T1 and T2 respectively indicate the first switching point and the second switching point of the gravity compensation value. T1-M L1 and T1+M H1Together they define the range of the transition zone near the first dividing line. Similarly, T2-M L2 and T2+M H2 Together they define the scope of the transition zone near the second dividing line.

[0026] The present invention also provides a system using the above-mentioned robot servo parameter adaptive method based on gravity compensation, including: a mechanical arm, a gravimeter and a controller, the mechanical arm is located on the gravimeter, and the controller is connected to the mechanical arm and the gravimeter.

[0027] A further technical solution is as follows: the mechanical arm is provided with a plurality of servo drivers.

[0028] Compared with the prior art, the present invention has the following beneficial effects: by calibrating the control parameters for each joint before the robot is installed, the present invention can ensure a more accurate response under different load conditions, thereby improving the initial performance of the system; by monitoring the load of each joint in real time during the operation of the robot, the system can obtain environmental change information in a timely manner and enhance the adaptability to dynamic loads. The gravity compensation value of each joint is calculated so that the servo system can make corresponding adjustments according to the actual load conditions, thereby improving the control accuracy; the servo system control parameters that drive the robot movement are dynamically calculated to ensure rapid adaptation in a changing environment, thereby improving the flexibility and robustness of the system; the combination of calibration and real-time feedback mechanism enables the servo system to maintain high performance in a complex environment, reducing the control instability caused by load changes.

[0029] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0031] Figure 1 A schematic flow chart of a robot servo parameter self-adaptation method based on gravity compensation provided by an embodiment of the present invention;

[0032] Figure 2 An example of control parameter calibration provided in an embodiment of the present invention is shown in FIG. Figure 1 ;

[0033] Figure 3 An example of control parameter calibration provided in an embodiment of the present invention is shown in FIG. Figure 2 ;

[0034] Figure 4 An example of control parameter calibration provided in an embodiment of the present invention is shown in FIG. Figure 3 ;

[0035] Figure 5 An example of control parameter calibration provided in an embodiment of the present invention is shown in FIG. Figure 4 ;

[0036] Figure 6 An example of control parameter calibration provided in an embodiment of the present invention is shown in FIG. Figure 5 ;

[0037] Figure 7 A curve diagram of control parameters of a servo system for dynamically calculating and driving the motion of a mechanical arm provided by an embodiment of the present invention;

[0038] Figure 8 A schematic diagram of a calculation process of a gravity compensation value provided by an embodiment of the present invention;

[0039] Fig. 9 A schematic block diagram of a robot servo parameter adaptive system based on gravity compensation provided by an embodiment of the present invention;

[0040] Fig.10 A schematic diagram comparing the startup process of the mechanical arm provided by the embodiment of the present invention before and after the adaptive method is used;

[0041] Fig.11 A schematic diagram comparing the front and rear stopping processes of a robotic arm using an adaptive method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0044] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0045] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0046] In the transmission system, the meshing degree of the harmonic reducer gears greatly affects the rigidity of the system. The load size is the main factor affecting the meshing degree of the reducer gears, so the servo system can adjust the control parameters by real-time monitoring of the load size to achieve the desired control effect. The robotic arm usually has a gravity compensation function. When the load size is known, the host computer can determine the force required for each joint servo through dynamic calculations and send it to the servo system. After receiving the gravity information, the servo system can select the appropriate control parameters for adjustment.

[0047] See also Figure 1 , Figure 1 The flow diagram of the robot servo parameter adaptive method based on gravity compensation provided by the embodiment of the present invention is applied to the server. By calibrating the control parameters for each joint under different load conditions before the installation of the robot arm, it is ensured that the servo system can adapt to various working conditions, thereby improving the robustness of the system. During the operation of the robot, the load condition of the robot arm is monitored in real time, and the gravity compensation value of each joint is calculated in time. This dynamic monitoring mechanism enhances the system's adaptability to environmental changes. The servo system control parameters that drive the robot arm to move are dynamically adjusted according to the load condition, so that the robot can automatically adjust when the load changes, thereby maintaining high efficiency and stability. The calibrated control parameters are optimized for different load conditions to ensure that the performance requirements can be met under three different load conditions of large, medium and small, thereby improving the scope of application of the system. The joint gravity compensation torque calculation formula is adopted, and the gravity compensation value can be calculated more accurately considering the dynamic parameters and force arm of each joint, thereby improving the control accuracy. By simplifying the calculation formula of the joint force arm, it is convenient to calculate in real time and improve the response speed, which is crucial for operations in complex working environments. By defining the transition zone range using the switching point of the gravity compensation value, the system can switch parameters more smoothly, reduce control fluctuations, and improve the stability of operation. The above technical innovations can maintain the stability and high performance of the servo system in a changing environment, making the robot more reliable when performing tasks and enhancing its application capabilities in complex scenarios.

[0048] Through these improvements, this method not only improves the robustness and performance of the servo system in dynamic environments, but also provides stronger support for the further development of robotics technology.

[0049] Figure 1FIG. 1 is a flow chart of a robot servo parameter self-adaptation method based on gravity compensation provided by an embodiment of the present invention. Figure 1 As shown, the method includes the following steps S110 to S130.

[0050] S110. Before installing the robot, send specific instructions to each joint of the robot under different load conditions to obtain the joint load-end speed and motor-end speed, and adjust and calibrate the control parameters. After obtaining the control effect that meets the requirements, store the calibrated control parameters as joint feature information in the joint's internal memory.

[0051] In this embodiment, before the robot is installed, the response of the joint under different loads is tested, and a set number of control parameters are selected from the test results to obtain calibrated control parameters, and the calibrated control parameters are stored as joint feature information in the joint's internal memory.

[0052] Specifically, the calibrated control parameters meet the performance requirements under three different load conditions: large, medium and small.

[0053] First, a response characteristic identification module is installed for each robot joint. The function of this module is to monitor and record the dynamic response of the joint under different loads in real time. By testing under different load conditions, the movement performance of the joint under various working conditions can be effectively obtained. The function of the response characteristic identification module is to analyze the response characteristics of the joint under different loads. In this process, when the joint receives the servo system operation instruction, its output end speed and motor end speed will be accurately recorded. In order to ensure that the control system can show the best control effect under various loads, the control parameters need to be adjusted accordingly.

[0054] Specifically, the system adjusts the load of the joint, usually dividing the load into several levels (for example, 5 equal parts) according to a certain ratio, that is, dividing the maximum load of the joint into five equal parts, so as to gradually adjust and optimize the control parameters. At each load level, the system will identify and debug the control parameters according to the predetermined target performance requirements, and finally select several sets of control parameters (usually 2-3 sets of optimal parameters) that can provide stable and good operating performance within the entire load range.

[0055] The servo parameter identification module is responsible for communicating with the servo system, sending specific operating instructions, and guiding the servo motor to work. During this process, the system collects data on the output speed and motor speed during joint movement through precise measuring tools and sensors. These data can help the system determine whether control parameters need to be adjusted to optimize performance. By comparing the performance under different loads, a parameter combination that can achieve good operating performance under the entire load range is selected.

[0056] In order to intuitively show the effect of calibration, Bode Plot is used to show the response of joints under different loads and different control parameters. Bode Plot is a commonly used frequency domain analysis tool that can show the relationship between the gain and phase of the system and the frequency. This is very helpful for analyzing the stability, frequency response and control accuracy of the system under different loads.

[0057] like Figures 2 to 6 As shown in the figure, taking a robot joint using a harmonic reducer as an example, the Bode diagram shows the dynamic response of the joint under different loads and control parameters. Through these diagrams, we can clearly see the amplitude and phase changes of the system response under different load conditions, and how these changes are optimized with the adjustment of control parameters. Specifically, compared Figure 2 , Figure 4 and Figure 5 It can be observed that when the load is small (29.88Nm), using the same PI parameters, the maximum amplitude-frequency response gain at the load end is as high as 3.75dB, and obvious resonance occurs. However, when the load is large (56.39Nm), the response gain at the load end is generally lower than -7dB in the frequency band exceeding 10Hz, resulting in a significant decrease in response speed. Figure 2 It can be seen that under light load conditions, reducing the PI control parameters can effectively reduce the resonance phenomenon at the load end; Figure 6 It shows that under heavy load conditions, increasing the P control parameter can effectively improve the response bandwidth of the load end. Through these observations, we can determine three sets of control parameters to meet the performance requirements under heavy, medium, and small load conditions. This ensures that the system can achieve ideal dynamic response and stability under different loads.

[0058] After the above identification process, the system can select the best control parameters in the entire load range from multiple sets of experimental data. Usually 2 to 3 sets of control parameters are selected, which can ensure that the joint operates stably and responsively during the change from minimum load to maximum load, and can maintain good control performance when the load fluctuates.

[0059] Through this calibration method, the robot can quickly adapt to different load environments after assembly, ensuring efficient and stable operation under various working conditions. This refined control parameter adjustment not only helps to improve the dynamic response accuracy of the joints, but also avoids excessive load on the system and reduces errors under different working conditions, thus optimizing the working efficiency of the entire robot.

[0060] In summary, the calibration of control parameters requires not only accurate load measurement and analysis, but also meticulous parameter adjustment and optimization. The impact of parameters on performance can be clearly demonstrated through graphical representations such as Bode diagrams, and the best combination of parameters can be ultimately selected to ensure that the robot system can operate stably under various actual workloads.

[0061] In this embodiment, the calibration is to find the appropriate control parameter matrix and gravity compensation reference value under different load conditions, namely PI1, PI2, PI3, T1, T2, M L1 、M H1 、M L2 and M H2 and pass it into the servo parameter tuning module.

[0062] S120, modeling and analyzing the mechanical structure of the robot, and calculating the mass, center of mass position, and motor shaft deflection angle dynamic parameters of the mechanical structure;

[0063] Modeling and analyzing the robot's mechanical structure involves accurately calculating the mass distribution of each arm, the center of mass position, and the deflection angle of the motor shaft. This analysis helps understand the dynamic characteristics of the entire robot system, such as how to cope with changes in different loads and how to adjust motor control to reduce unnecessary mechanical vibrations, thereby improving overall motion efficiency and accuracy.

[0064] By knowing the mass and center of mass location of each arm, designers can optimize the robot’s geometry and material selection to reduce energy consumption and increase load-carrying capacity.

[0065] Accurate dynamic modeling can help predict the robot's performance in actual work, avoid motion errors caused by inaccurate motor shaft deflection angles, and improve the accuracy of the control system.

[0066] Reasonable parameter calculation helps optimize the motor control algorithm, improve the robot's response speed to changes in the external environment, avoid excessive vibration or unnecessary energy waste, and improve overall work efficiency.

[0067] S130. During the operation of the robot, the load of the robot is monitored, and the gravity compensation value of each joint is calculated in combination with the robot's own posture information. Each joint uses a feedforward data channel to receive the gravity compensation value, and the data interpolation algorithm is used to subdivide and evenly distribute it to each control cycle.

[0068] In this embodiment, the gravity compensation value of each joint refers to the compensation performed to eliminate or reduce the influence of gravity on the robot arm during movement. By calculating the gravity value of the load, the controller can appropriately adjust the output of the servo drive so that the robot arm can maintain balance and stability when carrying different loads, thereby improving its operating accuracy and efficiency.

[0069] During the operation of the robot, the gravity measurement module can measure the load of the robot in real time. The single joint gravity load estimation module calculates the gravity compensation value of each joint and transmits it to the servo parameter setting module. The servo parameter setting module calculates the control parameters of the robot servo system module in real time based on the input data. The module uses the parameters to execute the instructions of the robot operation control module and drive the robot body to operate.

[0070] In one embodiment, the above-mentioned step S130 may include steps S131 - S132 .

[0071] S131. During the operation of the robot with the robotic arm, monitor the load of the robotic arm.

[0072] Specifically, during the operation of a robot with a robotic arm, the load of the robotic arm is determined by subtracting the gravity of the robotic arm itself from the total gravity of the robotic arm.

[0073] like Figure 8 As shown in the figure, the gravimeter transmits the gravity information of the load carried by the robot arm to the controller in real time. At the same time, the servo driver on the joint of the robot arm also acts as a sensor to feedback the robot arm's posture, running speed, output force, voltage, current and other status information to the controller. The controller combines the user's control instructions and the status information fed back by the system to send real-time control instructions to the servo driver. In addition, the controller calculates the gravity value of the load by subtracting the gravity of the body from the total gravity value received. The formula is as follows: G 负载 =G 总 -G 本体 .

[0074] S132. Calculate the gravity compensation value of each joint using the joint gravity compensation torque calculation formula according to the load of the robotic arm. Each joint uses a feedforward data channel to receive the gravity compensation value, and uses a data interpolation algorithm to subdivide and evenly distribute it to each control cycle.

[0075] In this embodiment, τ is used for each joint of the robot arm. n =A1·A2·...·A n ·T n ·T n+1 ·G 负载 Calculate the gravity compensation value, where A i Represents the dynamic parameters of the joint, T n Represents the moment arm of the joint, G 负载 Represents the load of the robot arm. The force arm of the joint is expressed by T n =cosθ·Len, where θ is the joint angle and Len is the length of the corresponding joint.

[0076] For example, using a common six-degree-of-freedom robot to calculate the gravity compensation value of each joint, the gravity compensation torque calculation formula for the 6th, 5th, 4th, 3rd, 2nd, and 1st joints is as follows:

[0077] τ6=A1*A2*A3*A4*A5*A6*T6*G 负载 ;

[0078] τ5=A1*A2*A3*A4*A5*T5*T6*G 负载 ;

[0079] τ4=A1*A2*A3*A4*T4*T5*T6*G 负载 ;

[0080] τ3=A1*A2*A3*T3*T4*T5*T6*G 负载 ;

[0081] τ2=A1*A2*T2*T3*T4*T5*T6*G 负载 ;

[0082] τ1=A1*T1*T2*T3*T4*T5*T6*G 负载 ;

[0083] Where T N =cosθ*Len includes the arm length and joint angle from the N axis to the (N+1) axis, which is used to calculate the gravitational moment value on joint N.

[0084] Matrix A N Contains the robot dynamic parameters in the direction from joint N to joint (N+1). A1*A2 is used to calculate the component of the gravity torque on joint 2 converted to the motor circumferential load.

[0085] Taking τ2 as an example, A1*A2 can calculate the posture of joint 2 relative to the base, and thus obtain the component size of the load torque of joint 2 in the circumferential direction of its motor. 负载 The load torque of the end load transmitted to joint 2 through joints 3, 4, 5, and 6 can be obtained. Combining the above two parts, the gravity compensation value of joint 2 can be obtained.

[0086] The controller uses robot dynamics to calculate the force required for each joint to overcome the gravity of the body and the gravity of the load, which is called the gravity compensation value and is sent to each joint. During operation, the joint uses the gravity load value as a basis to execute the parameter switching algorithm and adjust the PI control parameters in real time.

[0087] In this embodiment, in order to compensate for the influence of gravity in the robot movement, a feedforward data channel can be designed for each joint to receive the corresponding gravity compensation value. Then, these compensation values ​​are evenly distributed to each control cycle through the data interpolation algorithm. In this way, during the execution of each control cycle, the robot can predict and compensate for the influence caused by gravity in advance, thereby improving the response speed and stability of the control system.

[0088] Gravity compensation can effectively reduce external force disturbances caused by gravity, reduce load fluctuations in robot joints, and make the robot's movement more precise and smooth. Gravity compensation can reduce the load on the motor, allowing the robot to consume less energy when performing tasks. This is very beneficial for applications with high precision requirements, especially in long-term operations. The compensation value is evenly distributed to each control cycle through the data interpolation algorithm, which can make the robot's movement smoother and reduce the drastic changes and sudden vibrations that may occur in the joints during the movement. The feedforward control method can respond to possible gravity changes in advance by adjusting the motion compensation of each joint in real time, so that the robot's response speed when performing complex movements is improved. The subdivision and even distribution of gravity compensation data through the interpolation algorithm can simplify the implementation of the overall control algorithm, thereby improving the system's computational efficiency and reducing system latency.

[0089] S140. When the robot is working, each joint uses the gravity compensation value as the compensation amount of the torque loop instruction, and applies it to the motor and the load through the torque control loop; and the control parameters of the servo system that drives the movement of the robot arm are dynamically calculated based on the gravity compensation value and the adjusted control parameters.

[0090] In this embodiment, if Figure 8 As shown, using Calculate the control parameters of the servo system that drives the robot arm, where PI represents the matrix of the speed loop control parameters PI = [P v ,I v ], represents the control parameters of the servo system driving the robot arm, G comp Indicates the gravity compensation value. T1 and T2 respectively indicate the first switching point and the second switching point of the gravity compensation value. T1-M L1 and T1+M H1 Together they define the range of the transition zone near the first dividing line. Similarly, T2-M L2 and T2+M H2 Together they define the scope of the transition zone near the second dividing line.

[0091] In this embodiment, the PI control parameters of the speed loop are grouped according to different gravity compensation values. For example, when the gravity compensation value is small (lower than a certain threshold), a smaller speed PI parameter is selected; conversely, when the gravity compensation value is large, a larger speed PI parameter is selected.

[0092] Set the switching points T1 and T2 of the gravity compensation value to define the speed PI parameters for different load ranges. Specifically, T1-M L1 and T1+M H1 It constitutes the transition area near the first dividing line, T2-M L2 and T2+M H2 Then define the transition area near the second dividing line.

[0093] For example, a joint load is divided into three sections according to the test results. The first section is 0-30Nm, the second section is 30-50Nm, and the third section is 50-80Nm, that is, T1=30Nm, T2=50Nm, T3=80Nm, and M L1 =M H1 =M L2 =M H2 =M L3 =M H3 =5Nm. The first speed parameter PI1 = [P v1 =1000,I v1 =100]; the second speed PI2 = [P v2 =2000,I v2 =200]; The third speed parameter PI3 = [P v3 =3000,I v3 =300]. The load threshold is set to 5Nm.

[0094] At a certain moment, the gravity compensation value G comp =60Nm, T1+M H1 <G comp <T2-M L2 , belongs to the second PI range, so choose P v =P v2 =2000,I v =I v2 =200.

[0095] When the gravity compensation value is 50Nm at a certain moment, T1-M L1 <G comp <T1+M H1 , it belongs to the transition area between the second and third sections. At this time, the control parameters are calculated using linear interpolation:

[0096] Through the above settings, the system can flexibly adjust the control parameters of the speed loop according to the real-time gravity compensation value, thereby achieving more precise motion control.

[0097] See also Fig.10 and Fig.11 , in the start-stop cycle of a certain type of robot after grabbing a random load, the relationship between the speed command and the speed feedback was analyzed, and the response of the speed feedback under the single parameter tuning scheme and the method of this embodiment was compared. According to the data comparison in the picture, the speed command of the two tuning schemes is the same. However, compared with a single set of control parameters, the speed overshoot during the startup process of the method of this embodiment is reduced from 25% to 10%, and the overshoot during the stop process is reduced from 25% to 15%. Although the response time and stabilization time are basically the same, the dynamic response capability has been significantly optimized.

[0098] The above-mentioned robot servo parameter adaptive method based on gravity compensation can ensure more accurate response under different load conditions by calibrating the control parameters for each joint before installing the robot arm, thereby improving the initial performance of the system; the load of each joint is monitored in real time during the operation of the robot, so that the system can obtain environmental change information in a timely manner and enhance the adaptability to dynamic loads. The gravity compensation value of each joint is calculated so that the servo system can make corresponding adjustments according to the actual load conditions, thereby improving the control accuracy; the servo system control parameters that drive the movement of the robot arm are dynamically calculated to ensure rapid adaptation in a changing environment, thereby improving the flexibility and robustness of the system; combined with calibration and real-time feedback mechanisms, the servo system maintains high performance in complex environments and reduces control instability caused by load changes.

[0099] In one embodiment, see Fig. 9 , also provides a system using the above-mentioned robot servo parameter adaptive method based on gravity compensation, including: a robotic arm, a gravimeter and a controller, the robotic arm is located on the gravimeter, and the controller is connected to the robotic arm and the gravimeter.

[0100] Specifically, a plurality of servo drivers are provided on the robot arm.

[0101] The robot arm is driven by multiple servo drives to achieve movement and operation. To ensure accurate gravity measurement, the gravimeter fixed on the horizontal work surface of the robot arm can detect the gravity of the robot arm and its load at any time, and transmit the measurement results to the controller through cables. At the same time, the robot arm and the controller are connected by cables to transmit the robot arm's status data in real time, including posture, movement speed, voltage and current information. The controller issues control instructions based on the received data to adjust the operating status and behavior of the robot arm.

[0102] According to the influence of gravity compensation value on the response characteristics of servo system, this system realizes adaptive adjustment of servo parameters, fundamentally reduces the dependence on stiffness online identification algorithm, thus reducing the complexity of the system. In addition, the gravity compensation algorithm is not limited by the working state of the robot, which significantly reduces the risk of failure of adaptive method and response lag.

[0103] The system also integrates a gravimeter that can autonomously identify the load carried by the robot, avoiding the problem of traditional methods requiring the pre-setting of dynamic parameters, allowing it to better adapt to random load changes.

[0104] In addition, in one embodiment, a robot servo parameter self-adaptation device based on gravity compensation is also provided, including units corresponding to the above-mentioned robot servo parameter self-adaptation method based on gravity compensation, which will not be described in detail here.

[0105] The robot servo parameter adaptive device based on gravity compensation can be implemented in the form of a computer program.

[0106] The computer device 500 may be a server, wherein the server may be an independent server or a server cluster composed of multiple servers.

[0107] The computer device includes a processor, a memory and a network interface connected via a system bus, wherein the memory may include a non-volatile storage medium and an internal memory.

[0108] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can execute a robot servo parameter self-adaptation method based on gravity compensation.

[0109] The processor is used to provide computing and control capabilities to support the operation of the entire computer equipment.

[0110] The internal memory provides an environment for the operation of a computer program in a non-volatile storage medium. When the computer program is executed by a processor, the processor can execute a robot servo parameter self-adaptation method based on gravity compensation.

[0111] It should be understood that in the embodiments of the present application, the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0112] It can be understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiment can be completed by instructing the relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiment of the above method.

[0113] Therefore, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein when the computer program is executed by a processor, the processor executes the content corresponding to the robot servo parameter self-adaptation method based on gravity compensation.

[0114] The storage medium may be a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk, etc., which are computer-readable storage media that can store program codes.

[0115] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0116] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of each unit is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0117] The steps in the method of the embodiment of the present invention can be adjusted in order, combined and deleted according to actual needs. The units in the device of the embodiment of the present invention can be combined, divided and deleted according to actual needs. In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0118] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, terminal, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention.

[0119] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A robot servo parameter adaptive method based on gravity compensation, characterized in that: include: Before installing the robot, send specific instructions to each joint of the robot under different load conditions to obtain the joint load end speed and motor end speed, and adjust and calibrate the control parameters. After obtaining the control effect that meets the requirements, store the calibrated control parameters as joint feature information in the joint internal memory; Model and analyze the robot's mechanical structure, and calculate the mechanical structure's mass, center of mass position, and motor shaft deflection angle dynamic parameters; During the operation of the robot, the load of the robot is monitored, and the gravity compensation value of each joint is calculated based on the robot's own posture information; Each joint uses a feed-forward data channel to receive gravity compensation values, and uses a data interpolation algorithm to subdivide and evenly distribute them to each control cycle; When the robot is working, each joint uses the gravity compensation value as the compensation amount of the torque loop instruction, and applies it to the motor and the load through the torque control loop; and the control parameters of the servo system that drives the movement of the robot arm are dynamically calculated based on the gravity compensation value and the adjusted control parameters.

2. The robot servo parameter adaptive method based on gravity compensation according to claim 1, characterized in that: Before the robot is installed, a specific instruction is sent to each joint of the robot under different load conditions to obtain the joint load end speed and the motor end speed, and the control parameters are adjusted and calibrated at the same time. After obtaining the control effect that meets the requirements, the calibrated control parameters are stored as joint feature information in the joint internal memory, including: Before the robot is installed, the response of the joints under different loads is tested, and a set number of control parameters are selected from the test results to obtain calibrated control parameters, which are then stored as joint feature information in the joint's internal memory.

3. The robot servo parameter adaptive method based on gravity compensation according to claim 2, characterized in that: The calibrated control parameters meet the performance requirements under three different load conditions: large, medium and small.

4. The robot servo parameter adaptive method based on gravity compensation according to claim 1, characterized in that: During the operation of the robot, the load of the robot is monitored, and the gravity compensation value of each joint is calculated in combination with the posture information of the robot itself; Each joint uses a feedforward data channel to receive gravity compensation values, and uses a data interpolation algorithm to subdivide and evenly distribute them to each control cycle, including: During the operation of a robot with a robotic arm, monitor the load of the robotic arm; The gravity compensation value of each joint is calculated according to the joint gravity compensation torque calculation formula according to the load of the robotic arm. Each joint receives the gravity compensation value through a feedforward data channel and subdivides and evenly distributes it to each control cycle using a data interpolation algorithm.

5. The robot servo parameter adaptive method based on gravity compensation according to claim 4, characterized in that: The process of monitoring the load of the robot arm during operation of the robot with the robot arm includes: During the operation of a robot with a robotic arm, the total gravity of the robotic arm minus the gravity of the robotic arm itself is used to determine the load of the robotic arm.

6. The robot servo parameter adaptive method based on gravity compensation according to claim 4, characterized in that: The gravity compensation value of each joint is calculated according to the joint gravity compensation torque calculation formula according to the load of the robot arm, each joint receives the gravity compensation value through a feedforward data channel, and the data interpolation algorithm is used to subdivide and evenly distribute it to each control cycle, including: For each joint of the robot arm, τ n =A1·A2·...·A n ·T n ·T n+1 ·G 负载 Calculate the gravity compensation value, where A i Represents the dynamic parameters of the joint, T n Represents the moment arm of the joint, G 负载 Represents the load of the robotic arm. Each joint uses a feedforward data channel to receive the gravity compensation value, and uses a data interpolation algorithm to subdivide and evenly distribute it to each control cycle.

7. The robot servo parameter self-adaptation method based on gravity compensation according to claim 6, characterized in that: The moment arm of the joint is through T n =cosθ·Len, where θ is the joint angle and Len is the length of the corresponding joint.

8. The robot servo parameter self-adaptation method based on gravity compensation according to claim 7, characterized in that: When the robot is working, each joint uses the gravity compensation value as the compensation amount of the torque loop instruction, and applies it to the motor and the load through the torque control loop; and the control parameters of the servo system that drives the robot arm to move are dynamically calculated according to the gravity compensation value and the adjusted control parameters, including: use Calculate the control parameters of the servo system that drives the robot arm, where PI represents the matrix of the speed loop control parameters PI = [P v ,I v ], represents the control parameters of the servo system driving the robot arm, G comp Indicates the gravity compensation value. T1 and T2 respectively indicate the first switching point and the second switching point of the gravity compensation value. T1-M L1 and T1+M H1 Together they define the range of the transition zone near the first dividing line. Similarly, T2-M L2 and T2+M H2 Together they define the scope of the transition zone near the second dividing line.

9. A system using the robot servo parameter adaptive method based on gravity compensation as claimed in any one of claims 1 to 8, characterized in that: include: A mechanical arm, a gravimeter and a controller, wherein the mechanical arm is located on the gravimeter, and the controller is connected to the mechanical arm and the gravimeter.

10. The robot servo parameter adaptive system based on gravity compensation according to claim 9, characterized in that: The mechanical arm is provided with a plurality of servo drivers.

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