A force-position hybrid control method for a rope-cluster driven large-span spatial manipulator

Abstract

The present application provides a force-position hybrid control method for a rope cluster driven large-span space manipulator, which relates to the field of manipulator control technology. The method includes: establishing a kinematic model and a dynamic model of a rope cluster driven space manipulator based on preset model parameters, a preset kinematic model of the manipulator body, a preset mapping relationship between rope length and joint angle, and a preset mapping relationship between motor rotation angle and rope length; determining the desired trajectory of the manipulator joint angle and the desired trajectory of the rope tension according to the task requirements, kinematic model and dynamic model, and determining the desired trajectory of the motor rotation angle according to the kinematic model and the desired trajectory of the manipulator joint angle; determining the servo motor rotation angle command according to the model parameters, the desired trajectory of the motor rotation angle, the desired trajectory of the manipulator joint angle, the desired trajectory of the rope tension, the manipulator joint angle feedback and the rope tension feedback, and the force-position hybrid feedback motion controller, so as to control the rope cluster driven large-span space manipulator to move.

Description

Technical Field

[0001] The present application relates to the technical field of robot control, and for example, to a force-position hybrid control method for a rope-cluster driven large-span spatial robot. Background Art

[0002] With the development of science and technology, the application of long-distance space manipulators is becoming more and more extensive, and the requirements for precise control of manipulators are becoming higher and higher. When using space manipulators to complete the on-orbit assembly, construction and maintenance of large-scale space platforms and basic platforms such as future large-aperture space telescopes, large communication antennas, space solar power stations and deep space exploration transfer stations, the manipulator needs to have the key ability to be precisely controlled over long distances, and the rope cluster-driven long-span space manipulator came into being. The rope cluster-driven long-span space manipulator is a manipulator composed of modular tendon-driven joints in series. The tendon-driven joint of the manipulator contains a boom to achieve a longer moment arm between the tension rope cluster network and the joint rotation axis, which plays a role in torque amplification. With the help of rope cluster transmission, the drive device does not need to be located at the joint, which solves the problem of crowded design of traditional joints. At the same time, the tension rope cluster surrounds the entire joint, which can achieve the effect of enhancing joint stiffness. In addition, the arm itself is a lightweight truss structure, which reduces the mass of the entire arm. Therefore, under the same control distance design, the rope cluster driven large-span space manipulator is easier to take into account the characteristics of light weight, low inertia, high stiffness and large aspect ratio than the traditional space manipulator, and can better meet the needs of future large-scale space missions for long-distance on-orbit control.

[0003] The current single joint module of the rope cluster driven large-span space manipulator is driven by four motors. A group of rope clusters directly connects the drum and the boom driven by the motor, with high transmission efficiency and no slippage. The way the drum stores ropes can produce a large rope change. However, this design requires four ropes to coordinate two independent degrees of freedom to drive the joints. The ropes are easy to loosen and difficult to control. In the related art, two ropes on one side of the arm are used as driving ropes, using the position control mode, while the two ropes on the other side are used as antagonistic ropes, using the force control mode to control the large-span space manipulator. However, this control method may cause repeated switching between the position control and force control modes, resulting in unstable movement of the manipulator and repeated oscillations at the target position. Therefore, the current control effect is poor. Summary of the invention

[0004] The present application aims to provide a force-position hybrid control method for a rope-cluster driven large-span spatial manipulator.

[0005] According to one aspect of the present application, a force-position hybrid control method for a rope cluster driven large-span space manipulator is proposed, comprising: establishing a kinematic model and a dynamic model of the rope cluster driven large-span space manipulator based on preset model parameters, a preset kinematic model of the manipulator body, a preset mapping relationship between rope length and joint angle, and a preset mapping relationship between motor angle and rope length; determining the expected trajectory of the manipulator joint angle and the expected trajectory of the rope tension according to the task requirements, the kinematic model and the dynamic model; determining the expected trajectory of the motor angle according to the kinematic model and the expected trajectory of the manipulator joint angle; determining the servo motor angle command according to the model parameters, the expected trajectory of the motor angle, the expected trajectory of the manipulator joint angle, the expected trajectory of the rope tension, the measured manipulator joint angle feedback, the measured rope tension feedback, and a preset force-position hybrid feedback motion controller, so as to control the rope cluster driven large-span space manipulator to move according to the servo motor angle command.

[0006] According to some embodiments, based on preset model parameters, a preset robot body kinematic model, a preset rope length and joint angle mapping relationship, and a preset motor angle and rope length mapping relationship, a kinematic model and a dynamic model of a rope cluster driven large-span spatial robot arm are established, including: obtaining a rope length and joint angle mapping relationship, a motor angle and rope length mapping relationship, a robot body kinematic model and model parameters; wherein the model parameters include kinematic model parameters and dynamic model parameters; determining the rope length and joint angle mapping relationship, the motor angle and rope length mapping relationship, the robot body kinematic model and kinematic model parameters as a kinematic model; and determining the dynamic model based on the Lagrangian method and dynamic model parameters.

[0007] According to some embodiments, the dynamic model parameters include a rope linear stiffness coefficient and a rope linear damping coefficient; the above method also includes: determining the rope tension corresponding to each of the multiple ropes based on a preset rope tension determination method, a rope linear stiffness coefficient, and a rope linear damping coefficient, so as to determine the dynamic model according to the rope tension, the dynamic model parameters and the Lagrangian method.

[0008] According to some embodiments, the above method also includes: determining the composition data of joints, hangers, ropes and arm levers corresponding to each set of joint-related composition information based on multiple sets of preset joint-related composition information corresponding to multiple joints in a rope cluster-driven large-span spatial robot arm; determining the mapping relationship between rope length and joint angle according to the composition data of joints, hangers, ropes and arm levers and a preset mapping relationship setting method.

[0009] According to some embodiments, the expected trajectory of the joint angle of the manipulator and the expected trajectory of the rope tension are determined according to the task requirements, kinematic model and dynamic model, including: determining the initial moment, end moment and pre-tension in the motion task corresponding to the rope cluster driven large-span spatial manipulator according to the task requirements; wherein the pre-tension is the rope tension at the initial moment; obtaining the joint angles at the initial moment and the end moment; determining the expected trajectory of the joint angle of the manipulator according to the kinematic model and the joint angles; determining the static equilibrium relationship according to the dynamic model; determining the expected tension at the end moment according to the static equilibrium relationship and the task requirements; determining the expected trajectory of the rope tension according to the kinematic model, the pre-tension and the expected tension at the end moment.

[0010] According to some embodiments, determining the expected trajectory of the motor angle according to the kinematic model and the expected trajectory of the robot arm joint angle includes: inputting the expected trajectory of the robot arm joint angle into the kinematic model, and outputting the expected trajectory of the motor angle.

[0011] According to some embodiments, a servo motor angle command is determined based on model parameters, an expected trajectory of a motor angle, an expected trajectory of a robot arm joint angle, an expected trajectory of rope tension, measured robot arm joint angle feedback, measured rope tension feedback, and a preset force-position type hybrid feedback motion controller to control a rope cluster-driven large-span space robot to move according to the servo motor angle command, including: obtaining the relationship between the arm shape and the rope retraction and release characteristics of the rope cluster-driven large-span space robot, the robot arm joint angle feedback, and the rope tension feedback; determining the expected joint angle and the expected rope tension at the current moment according to the expected trajectory of the robot arm joint angle and the expected trajectory of the rope tension; determining the actual joint angle difference and the actual rope tension error according to the expected joint angle, the robot arm joint angle feedback, the expected rope tension, and the rope tension feedback; inputting the model parameters, the expected trajectory of the motor angle, the actual joint angle difference, and the actual rope tension error into the force-position type hybrid feedback motion controller to output a determined servo motor angle command; and controlling the rope cluster-driven large-span space robot to move according to the servo motor angle command.

[0012] According to one aspect of the present application, a rope cluster driven large-span space manipulator force-position hybrid control system is proposed, comprising:

[0013] A model building module is used to build a kinematic model and a dynamic model of a rope cluster driven large-span space manipulator based on preset model parameters, a preset kinematic model of the manipulator body, a preset mapping relationship between rope length and joint angle, and a preset mapping relationship between motor rotation angle and rope length;

[0014] The trajectory generation module is used to determine the expected trajectory of the robot arm joint angle and the expected trajectory of the rope tension according to the task requirements, kinematic model and dynamic model; and determine the expected trajectory of the motor rotation angle according to the kinematic model and the expected trajectory of the robot arm joint angle;

[0015] The instruction generation module is used to determine the servo motor angle instruction based on model parameters, the expected trajectory of the motor angle, the expected trajectory of the robot arm joint angle, the expected trajectory of the rope tension, the measured robot arm joint angle feedback, the measured rope tension feedback and the preset force-position hybrid feedback motion controller, so as to control the rope cluster to drive the large-span spatial robot to move according to the servo motor angle instruction.

[0016] Optionally, the model building module is specifically used for:

[0017] Obtaining the mapping relationship between rope length and joint angle, the mapping relationship between motor rotation angle and rope length, the kinematic model and model parameters of the robot body; wherein the model parameters include kinematic model parameters and dynamic model parameters;

[0018] The mapping relationship between the rope length and the joint angle, the mapping relationship between the motor angle and the rope length, the kinematic model of the robot body and the kinematic model parameters are determined as a kinematic model;

[0019] The kinetic model is determined based on the Lagrangian method and the kinetic model parameters.

[0020] Optionally, the dynamic model parameters include a rope linear stiffness coefficient and a rope linear damping coefficient; the rope cluster driven large-span spatial manipulator force-position hybrid control system also includes a rope tension determination module for:

[0021] Based on the preset rope tension determination method, rope linear stiffness coefficient, and rope linear damping coefficient, rope tensions corresponding to each of the plurality of ropes are determined, so as to determine the dynamic model according to the rope tensions, dynamic model parameters, and the Lagrangian method.

[0022] Optionally, the rope cluster driven large-span spatial manipulator force-position hybrid control system further includes a mapping relationship determination module, which is used to:

[0023] Based on multiple groups of preset joint-related component information corresponding to multiple joints in the rope-cluster driven large-span spatial manipulator, component data of joints, suspension rods, ropes and arm rods corresponding to each group of joint-related component information are determined;

[0024] The mapping relationship between the rope length and the joint angle is determined according to the component data of the joint, the boom, the rope and the arm and the preset mapping relationship setting method.

[0025] Optionally, the trajectory generation module is specifically used to determine the expected trajectory of the joint angle of the manipulator and the expected trajectory of the rope tension according to the task requirements, the kinematic model and the dynamic model:

[0026] According to the task requirements, determine the initial moment, end moment and preload force in the motion task corresponding to the rope cluster driving the large-span space manipulator; the preload force is the rope tension at the initial moment;

[0027] Get the joint angles at the initial and end times;

[0028] Determine the expected trajectory of the robot's joint angles based on the kinematic model and joint angles;

[0029] According to the dynamic model, determine the static equilibrium relationship;

[0030] Determine the expected tension at the end based on the static balance relationship and task requirements;

[0031] The expected trajectory of the rope tension is determined based on the kinematic model, the preload force and the expected tension at the end moment.

[0032] Optionally, the trajectory generation module is specifically used to determine the expected trajectory of the motor angle according to the kinematic model and the expected trajectory of the robot arm joint angle:

[0033] The desired trajectory of the robot arm joint angles is input into the kinematic model, and the desired trajectory of the motor angle is output.

[0034] Optionally, the instruction generation module is specifically used for:

[0035] Obtain the relationship between the arm shape and rope retraction and release characteristics of the rope cluster-driven large-span space manipulator, the manipulator joint angle feedback and the rope tension feedback;

[0036] Determine the expected joint angle and expected rope tension at the current moment according to the expected trajectory of the robot arm joint angle and the expected trajectory of the rope tension;

[0037] Determine an actual joint angle difference and an actual rope tension error according to the desired joint angle, the robot arm joint angle feedback, the desired rope tension and the rope tension feedback;

[0038] The model parameters, the desired trajectory of the motor rotation angle, the actual joint angle difference and the actual rope tension error are input into the force-position hybrid feedback motion controller to output a determined servo motor rotation angle command;

[0039] The control rope cluster drives the large-span space robot to move according to the servo motor angle command.

[0040] According to one aspect of the present application, an electronic device is proposed, which includes: a processor; a memory storing a computer program, and when the computer program is executed by the processor, the processor executes the feedback control method of the rope cluster driven large-span spatial manipulator as described above.

[0041] According to one aspect of the present application, a non-transitory computer-readable medium is provided, on which readable instructions are stored. When the instructions are executed by a processor, the processor executes the feedback control method of a rope cluster driven large-span spatial manipulator as described above.

[0042] It should be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the present application.

[0043] Beneficial effects:

[0044] Through the above-mentioned embodiments provided by the present application, by integrating the preset model parameters, the kinematic model of the robot body, the mapping relationship between the rope length and the joint angle, and the mapping relationship between the motor angle and the rope length, an accurate and comprehensive kinematic and dynamic model of a rope cluster-driven large-span space robot can be established. Based on the task requirements and the preset polynomial interpolation method, combined with the kinematic model and the dynamic model, the expected trajectory of the robot joint angle and the expected trajectory of the rope tension can be accurately calculated. By introducing the measured feedback of the robot joint angle and the rope tension, the actual motion state of the robot and the tension of the rope can be monitored in real time, and the servo motor angle command can be dynamically adjusted according to these feedback data. At the same time, the introduction of position and tension feedback can monitor the actual motion state of the robot and the tension of the rope in real time, so that the robot can move accurately according to the expected trajectory, meet the task requirements, and can timely detect and adjust the slack state of the rope, prevent motion errors or system instability caused by rope slack, and improve the feedback control effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without exceeding the scope of protection required by the present application.

[0046] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application;

[0047] Figure 2 A flow chart of a force-position hybrid control method for a rope-cluster driven large-span space manipulator provided in an embodiment of the present application;

[0048] Figure 3A control system block diagram corresponding to any driving rope provided in the embodiments of the present application;

[0049] Figure 4 A schematic diagram of joint numbering provided for an embodiment of the present application;

[0050] Figure 5 A schematic diagram of joint simulation results provided in an embodiment of the present application;

[0051] Figure 6 A schematic diagram of rope tension simulation results provided in an embodiment of the present application;

[0052] Figure 7 A schematic diagram of the joint angle tracking error simulation results provided in an embodiment of the present application;

[0053] Figure 8 A block diagram of a force-position hybrid control system of a rope cluster driven large-span space manipulator provided in an embodiment of the present application;

[0054] Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this application will be comprehensive and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted.

[0056] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0057] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0058] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0059] It should be understood that although the terms first, second, third, etc. may be used herein to describe various components, these components should not be limited by these terms. These terms are used to distinguish one component from another component. Therefore, the first component discussed below can be referred to as the second component without departing from the teachings of the concepts of the present application. As used herein, the term "and / or" includes any one of the associated listed items and all combinations of one or more.

[0060] Figure 1 Schematic diagram of application scenarios provided by embodiments of the present application. In the on-orbit assembly, construction and maintenance of large space platforms and infrastructure, the rope cluster driven large-span space manipulator of the present application can be used. The rope cluster driven large-span space manipulator can be composed of a base platform, an arm, a suspension rod, ropes, a rotary joint, a clamp, and a rope drive device (not shown in the figure). Figure 1 In the application scenario shown, the force-position hybrid control method of the rope cluster driven large-span space manipulator can be built on the feedback control server. The feedback control server can establish various models and determine the expected trajectory based on the task requirements and preset measures such as polynomial interpolation methods, and then obtain the servo motor angle command, so as to send the servo motor angle command to the control device to control the ropes, arms, booms, and rotary joints on the rope cluster driven large-span space manipulator to perform corresponding movements.

[0061] For specific implementation methods, please refer to the following embodiments.

[0062] Figure 2 This is a flow chart of the force-position hybrid control method of a rope cluster driven large-span space manipulator provided in an embodiment of the present application. The method of this embodiment can be applied to the feedback control server in the above application scenario. Figure 2 As shown, the method includes: step S20, step S21 and step S22.

[0063] In step S20, the kinematic model and dynamic model of the rope cluster driven large-span spatial robot are established based on preset model parameters, preset robot body kinematic model, preset rope length and joint angle mapping relationship, preset motor angle and rope length mapping relationship.

[0064] The rope cluster driven large span space manipulator in the present application is a manipulator with a large working span that adopts a rope cluster transmission mechanism. The preset model parameters may include the distance between the two joint rotation axes corresponding to the joints, the distance between the drum rotation axis and the joint rotation axis, the arm length, the boom height, the drum radius, the transmission ratio of the reducer between the motor and the drum, etc. The preset manipulator body kinematic model is a conventional multi-link manipulator kinematic model.

[0065] The rope cluster robot drives the rotation of the joints by retracting and releasing the rope. When the rope is pulled, it moves along a specific path (usually through a pulley or guide device), thereby driving the joint to rotate. Since there is a direct physical connection between the change in rope length and the rotation angle of the joint, the mapping relationship between rope length and joint angle can be pre-set.

[0066] In the rope cluster robot, the motor is used as a power source to drive the rotation of the robot joints by driving the rope to be retracted and released. When the motor rotates, it converts the rotation into the linear motion of the rope through the transmission mechanism (such as the reducer, drum, etc.), thereby changing the length of the rope. Therefore, the mapping relationship between the motor rotation angle and the rope length can be pre-set.

[0067] The kinematic model of the rope-cluster driven large-span space manipulator is used to describe the motion state of the manipulator, that is, the change of parameters such as position, velocity and acceleration over time. The dynamic model is used to describe the mechanical characteristics of the manipulator during the motion, including the influence of factors such as force, torque and mass distribution on the motion of the manipulator.

[0068] According to the example embodiments, on the basis of a preset kinematic model of the robot body, the model can be adjusted based on preset model parameters and a preset mapping relationship between rope length and joint angle, and a preset mapping relationship between motor angle and rope length, to obtain a kinematic model and a dynamic model of a rope cluster driven large-span spatial robot.

[0069] In some implementations, the adjustment method of the dynamic model and the kinematic model compared to the kinematic model of the robot body can be pre-set, and then the model parameters, the mapping relationship between rope length and joint angle, and the mapping relationship between motor angle and rope length can be substituted into the calculation process of each part corresponding to the adjustment method to obtain the dynamic model and the kinematic model.

[0070] In step S21, the expected trajectory of the robot arm joint angle and the expected trajectory of the rope tension are determined according to the task requirements, the kinematic model and the dynamic model; the expected trajectory of the motor angle is determined according to the kinematic model and the expected trajectory of the robot arm joint angle.

[0071] In this application, the task requirements can be sent to the feedback control server by relevant staff or pre-set on the feedback control server. The task requirements can be to drive a large-span space robot arm to move smoothly from an initial position to a target position by a rope cluster. The expected trajectory of the motor angle is the set of positions or postures that the rotor output shaft of the motor is expected to reach during the movement of the motor, and these positions or postures usually change over time.

[0072] In some implementations, task requirements may be input into the kinematic model and the dynamic model to output the desired trajectory of the robot arm joint angle and the desired trajectory of the rope tension, and then the desired trajectory of the robot arm joint angle may be input into the kinematic model to output the desired trajectory of the motor angle.

[0073] In other implementations, a polynomial interpolation method can be used to determine the expected trajectory of the robot arm joint angle and the expected trajectory of the rope tension. The polynomial interpolation method is a method of using the function values ​​of the function f(x) at several known points in a certain interval to make an appropriate specific function, and using the value of a specific function at other points in the interval as an approximate value of the function f(x). If this specific function is a polynomial, it is called polynomial interpolation. The task requirements and the preset polynomial interpolation method can be input into the dynamic model to output the expected trajectory of the robot arm joint angle and the expected trajectory of the rope tension. The expected trajectory of the robot arm joint angle and the expected trajectory of the rope tension can be expressed in the form of a polynomial. The expected trajectory of the robot arm joint angle and the expected trajectory of the rope tension can be input into the kinematic model to directly output the expected trajectory of the motor angle.

[0074] In step S22, the servo motor angle command is determined based on the model parameters, the expected trajectory of the motor angle, the expected trajectory of the robot joint angle, the expected trajectory of the rope tension, the measured robot joint angle feedback and the measured rope tension feedback, and the preset force-position hybrid feedback motion controller to control the rope cluster to drive the large-span spatial robot to move according to the servo motor angle command.

[0075] In the present application, the encoder can measure the actual joint angle, and the tension sensor can measure the actual rope tension, and the two actually measured data are used as the measured robot arm joint angle feedback and the measured rope tension feedback. The servo motor angle command can be a command for controlling the servo motor to rotate to a specific angle. The force-position hybrid feedback motion controller can be a pre-set device that performs motion control based on rope tension feedback, joint position feedback, and prior knowledge of the arm shape.

[0076] According to the exemplary embodiment, the corresponding determination method of the servo motor angle command can be preset under different model parameters, expected trajectory of motor angle, expected trajectory of robot arm joint angle, expected trajectory of rope tension, measured robot arm joint angle feedback, and measured rope tension feedback. After the corresponding determination method is matched, the model parameters, the expected trajectory of motor angle, the expected trajectory of robot arm joint angle, the expected trajectory of rope tension, the measured robot arm joint angle feedback, and the measured rope tension feedback are processed, and then the processed data is input into the preset force-position type hybrid feedback motion controller to obtain the servo motor angle command, so as to control the rope cluster to drive the large-span space robot to move according to the servo motor angle command.

[0077] In some implementations, reference may be made to Figure 3 In the control system block diagram corresponding to any one of the drive ropes shown, the encoder can measure the joint angle measurement value, that is, the measured robot arm joint angle feedback; the dynamometer can measure the rope tension measurement value, that is, the measured rope tension feedback. The robot arm joint angle feedback measured by the encoder can be input into the preset proportional-integral-derivative controller (PID) together with the expected joint angle position (that is, the current position corresponding to the expected trajectory of the robot arm joint angle). Then PID can process the input data, and then mix the pre-acquired and stored prior knowledge of the "arm type" with the kinematic feedforward control (that is, the expected trajectory of the motor angle in this application) as the angle command, and input it into the motor PID for closed-loop control, thereby controlling the rope cluster-driven large-span spatial robot.

[0078] This application can establish an accurate and comprehensive kinematic and dynamic model of a rope-cluster-driven large-span space manipulator by integrating preset model parameters, the kinematic model of the manipulator body, the mapping relationship between rope length and joint angle, and the mapping relationship between motor angle and rope length. Based on task requirements and preset polynomial interpolation methods, combined with kinematic models and dynamic models, the expected trajectory of the manipulator joint angle and the expected trajectory of the rope tension can be accurately calculated. By introducing the measured feedback of the manipulator joint angle and rope tension, the actual motion state of the manipulator and the tension of the rope can be monitored in real time, and the servo motor angle command can be dynamically adjusted based on these feedback data. At the same time, the introduction of position and tension feedback can monitor the actual motion state of the manipulator and the tension of the rope in real time, so that the manipulator can move accurately according to the expected trajectory to meet task requirements, and can promptly detect and adjust the slack state of the rope to prevent motion errors or system instability caused by rope slack, thereby improving the feedback control effect.

[0079] According to some embodiments, step S20 can be specifically implemented through the following steps: obtaining the mapping relationship between rope length and joint angle, the mapping relationship between motor angle and rope length, the kinematic model of the robot body and model parameters; wherein the model parameters include kinematic model parameters and dynamic model parameters; determining the mapping relationship between rope length and joint angle, the mapping relationship between motor angle and rope length, the kinematic model of the robot body and the kinematic model parameters as a kinematic model; determining the dynamic model based on the Lagrangian method and the dynamic model parameters.

[0080] In the present application, the mapping relationship between rope length and joint angle, the mapping relationship between motor angle and rope length, the kinematic model of the robot body and model parameters can be pre-set and stored. The model parameters can be divided into kinematic model parameters for establishing a kinematic model and dynamic model parameters for establishing a dynamic model according to the usage.

[0081] According to the example embodiment, the pre-stored mapping relationship between rope length and joint angle, the mapping relationship between motor rotation angle and rope length, the kinematic model of the robot body and the model parameters can be obtained. Then, the mapping relationship between rope length and joint angle, the mapping relationship between motor rotation angle and rope length, the kinematic model of the robot body and the kinematic model parameters can be used as the overall content of the kinematic model. The dynamic model parameters can be derived using the Lagrangian method to obtain the dynamic model.

[0082] In some implementations, reference Figure 4 The joint numbering diagram shown is for joints, and the two arms are named arm and boom , the boom is named as boom , four ropes named ropes ,rope ,rope and ropes The mapping relationship between the drive rope length and the joint angle is:

[0083]

[0084]

[0085]

[0086]

[0087] in, and are the rotation angles of the two joint rotation axes (not shown in the figure) corresponding to the i-th shutdown, is the distance from the reel rotation axis (not shown in the figure) to the joint rotation axis, is the distance between the two joint rotation axes of each revolute joint, is the boom height, is the roll radius.

[0088] The mapping relationship between the motor angle and the rope length is:

[0089]

[0090] in, is the set vector of all motor angles, , is the set vector of all joint rotation angles, , is the transmission ratio of the reducer between the motor and the drum, is the rope length of all driving ropes at the initial moment, is the rope length of all driving ropes at the current moment, is the angle between the line connecting the tangent point of all driving ropes to the drum and the center of the drum at the initial moment and the arm, It is the angle formed by the line connecting the tangent point of all driving ropes to the drum and the center of the drum at the current moment and the arm.

[0091] The kinetic model is:

[0092]

[0093] in, is the inertia matrix corresponding to the robot body-reel drive system, is the inertia matrix corresponding to the motor-reel drive system. is the inertial coupling constant matrix, are the centrifugal force and Coriolis force vectors, is the rope tension vector, is the friction torque at the joint of the robot arm, is the friction torque in the drive system, is the motor torque, is the Jacobian matrix.

[0094] The parameters in the above model can be pre-set and stored, and can be directly obtained when needed.

[0095] This application can establish a comprehensive and accurate kinematic and dynamic model of a rope cluster-driven large-span space manipulator by integrating the mapping relationship between rope length and joint angle, the mapping relationship between motor angle and rope length, the kinematic model of the manipulator body, and the model parameters. This integration makes the control of the manipulator more precise, which helps to improve the operating efficiency and accuracy of the manipulator in a complex space environment. The establishment of the dynamic model is based on the Lagrangian method, which takes into account the dynamic characteristics of the manipulator during movement, such as inertia, friction, etc. This makes it possible to conduct an in-depth analysis of the dynamic performance of the manipulator, and then optimize the dynamic response of the manipulator by adjusting the model parameters or designing algorithms to improve its stability and robustness.

[0096] According to some embodiments, the dynamic model parameters include a rope linear stiffness coefficient and a rope linear damping coefficient. The process of establishing the kinematic model and the dynamic model may further include the following steps: based on a preset rope tension determination method, a rope linear stiffness coefficient, and a rope linear damping coefficient, determining the rope tension corresponding to each of the plurality of ropes, so as to determine the dynamic model according to the rope tension, the dynamic model parameters and the Lagrangian method.

[0097] In this application, the dynamic model parameters also include parameters such as the mass and inertia parameters of the boom and the suspension rod. The rope tension is calculated as follows:

[0098]

[0099] in, and are the rope linear stiffness coefficient and rope linear damping coefficient, respectively. and are the actual length and the length before deformation of the i-th rope, and Pre-calculation can be performed according to the kinematic model.

[0100] According to the exemplary embodiment, according to the above calculation process, the rope tension corresponding to each of the plurality of ropes can be obtained, so as to facilitate determining the dynamic model according to the rope tension, the dynamic model parameters and the Lagrangian method.

[0101] This application achieves an accurate description of the dynamic characteristics of the rope system by introducing a series of key dynamic model parameters, including the rope linear stiffness coefficient and the rope linear damping coefficient. Further using these parameters, combined with the preset rope tension determination method, the tension on each rope can be accurately calculated. Through accurate rope tension calculation, combined with the Lagrangian method, a more accurate and closer to the actual physical situation dynamic model can be constructed.

[0102] According to some embodiments, the mapping relationship between rope length and joint angle can be set, which can be specifically achieved through the following steps: based on multiple groups of preset joint-related composition information corresponding to multiple joints in a rope cluster-driven large-span spatial robot arm, the composition data of the joints, hangers, ropes and arm levers corresponding to each group of joint-related composition information are determined; according to the composition data of the joints, hangers, ropes and arm levers and the preset mapping relationship setting method, the mapping relationship between rope length and joint angle is determined.

[0103] In this application, the joint number, boom number, rope number, arm number and other information of each group of joints can be preset according to the design drawings of the rope cluster driven large-span space manipulator. The numbering method can refer to Figure 4 Then, based on the actual assembly situation, the type, position, and rotation range of the joints; the length, material, and installation position of the boom; the diameter and preload of the rope; the length and cross-sectional shape of the boom, and other information can be obtained, and this information can be used as a whole as the component data.

[0104] Data model establishment, formula derivation, etc. can be used as a preset mapping relationship setting method, and then the component data is processed accordingly to obtain the rope length and joint angle mapping relationship. In some implementations, a mathematical equation between the rope length and the joint angle can be established based on spatial geometry, and then the mapping relationship is obtained by solving the equation.

[0105] This application obtains and analyzes multiple sets of preset joint association composition information corresponding to multiple joints in the robot arm, and accurately obtains the composition data of the joints, booms, ropes and arm rods in each set of joint associations. Based on these data, combined with the preset mapping relationship setting method, the mapping relationship between the rope length and the joint angle can be accurately established. This precise modeling and mapping provides a solid foundation for the subsequent motion control of the robot arm.

[0106] According to some embodiments, step S21 can be specifically implemented by the following steps: according to the task requirements, determine the initial moment, end moment and preload force in the motion task corresponding to the rope cluster driven large-span spatial manipulator; wherein the preload force is the rope tension at the initial moment; according to inverse kinematics, obtain the joint angles at the initial moment and the end moment; according to the polynomial interpolation method and the joint angles, determine the expected trajectory of the manipulator joint angles; according to the dynamic model, determine the static equilibrium relationship; according to the static equilibrium relationship and the task requirements, determine the expected tension at the end moment; according to the polynomial interpolation method, the preload force and the expected tension at the moment, determine the expected trajectory of the rope tension.

[0107] In this application, the kinetic model is:

[0108]

[0109] Based on this, considering the static situation where both the velocity and acceleration are 0, the static equilibrium relationship can be obtained, namely:

[0110]

[0111] According to the example embodiment, the motion task that the robot needs to complete can be extracted from the task requirements, including but not limited to the starting position, target position, motion time, and preload, etc. The preload can be the rope tension set at the initial moment. At the initial moment, the initial angles of each joint of the robot can be measured by sensors, and the target joint angles that should be reached at the end moment can be obtained from the task requirements. According to the dynamic model of the robot, the force conditions of the robot during the movement are analyzed, and a static equilibrium equation is established. The static equilibrium equation can be used to determine the relationship between the tension of each rope and parameters such as the joint angle and arm position during the movement of the robot. Combining the task requirements (such as target position, posture, etc.) and the static equilibrium relationship, the expected tension of each rope of the robot at the end moment can be calculated.

[0112] In some implementations, the joint angles can be directly input into the kinematic model to directly output the desired trajectory of the robot arm joint angles. The preload force and the desired tension at the end time can be input into the dynamic model to directly output the desired trajectory of the rope tension.

[0113] In other implementations, a polynomial interpolation method can be used to generate a smooth joint angle transformation trajectory based on the joint angle data at the initial moment and the end moment, and the set movement time. In some implementations, the polynomial interpolation can select a suitable order to meet the smoothness and accuracy requirements of the robot movement. The generated polynomial function is determined as the desired trajectory of the robot joint angle, that is, the first required polynomial.

[0114] The polynomial interpolation method is also used to generate a smooth rope tension change trajectory according to the preload at the initial moment, the desired tension at the end moment, and the set movement time. The generated polynomial function is determined as the desired trajectory of the rope tension, that is, the second demand polynomial.

[0115] By combining task requirements, kinematic models and dynamic models, the present application can accurately plan the expected trajectory of the joint angle and the expected trajectory of the rope tension of the manipulator when performing a specific task. This ensures that the manipulator can operate according to the expected path and force during the movement, and improves the accuracy and stability of the operation. Combining the joint angles at the initial and end moments, and the preload (i.e., rope tension) at the initial moment, helps the manipulator reach a stable state before starting, while ensuring that it can stop with a suitable posture and force at the end of the task, avoiding unnecessary vibration or impact of the manipulator during the movement. By determining the static equilibrium relationship through the dynamic model, the force of the manipulator during the movement can be further accurately controlled. The use of this equilibrium relationship helps to ensure that the manipulator can remain stable when subjected to external loads, while reducing unnecessary energy consumption and wear. The expected trajectory of the rope tension is determined based on the kinematic model, the preload and the expected tension at the end moment. This dynamic adjustment strategy can ensure the continuity and smoothness of the rope tension of the manipulator during the movement, thereby avoiding the loss of control or damage of the manipulator due to sudden changes in tension.

[0116] According to some embodiments, step S22 may be specifically implemented by the following steps: inputting the expected trajectory of the robot arm joint angle into the kinematic model, and outputting the expected trajectory of the motor rotation angle.

[0117] According to the exemplary embodiment, the desired trajectory of the joint angle of the robot arm can be input into the kinematic model, and the desired trajectory of the motor angle can be directly output. This desired trajectory should ensure that the robot arm can smoothly and accurately track the desired trajectory of the joint angle in actual movement and meet the requirements of the rope tension.

[0118] By inputting the expected trajectory of the robot arm joint angle into the kinematic model, the application can accurately calculate the expected trajectory of the motor angle. Accurate motor angle control helps optimize the motion performance of the robot arm. By ensuring that the motor rotates according to the expected trajectory, the vibration and deviation of the robot arm during movement can be reduced, and the smoothness and accuracy of the movement can be improved. This helps to improve the work efficiency and work quality of the robot arm.

[0119] According to some embodiments, step S22 can be implemented by the following steps: obtaining the relationship between the arm shape and the rope retraction and release characteristics of the rope cluster driven large-span space manipulator, the manipulator joint angle feedback and the rope tension feedback; determining the expected joint angle and the expected rope tension at the current moment according to the expected trajectory of the manipulator joint angle and the expected trajectory of the rope tension; determining the actual joint angle difference and the actual rope tension error according to the expected joint angle, the manipulator joint angle feedback, the expected rope tension and the rope tension feedback; inputting the model parameters, the expected trajectory of the motor angle, the actual joint angle difference and the actual rope tension error into the force-position type hybrid feedback motion controller to output and determine the servo motor angle command; controlling the rope cluster driven large-span space manipulator to move according to the servo motor angle command.

[0120] In the present application, the arm structure of the rope cluster driven large-span space manipulator determines the layout and direction of the rope. Different arm structures may cause changes in the friction and stretching characteristics of the rope during the retraction and release process. The more joint degrees of freedom of the manipulator, the more ropes are usually needed to drive these joints. This will increase the complexity of rope retraction and the requirements for the control system. At the same time, the increase in joint degrees of freedom may also cause interference and entanglement problems of the rope during the retraction and release process, which requires special design and optimization to avoid. The arm length and span of the rope cluster driven large-span space manipulator directly affect the length and retraction range of the rope. Longer arm lengths and spans may require longer ropes to drive, which will increase the weight and inertia of the rope, and affect the retraction and release speed and accuracy of the rope. Therefore, based on the influence of the above arm type on the rope retraction and release characteristics, the relationship between the arm type and the rope retraction and release characteristics of the rope cluster driven large-span space manipulator can be pre-set.

[0121] The joint angle feedback and the rope tension feedback of the robot arm can be detected by pre-set devices such as sensors. The joint angle and the rope tension in the expected trajectory of the robot arm joint angle and the expected trajectory of the rope tension change with time, and the expected joint angle and the expected rope tension at the current moment can be directly obtained from the trajectory.

[0122] According to the example embodiment, the expected joint angle is subtracted from the arm joint angle feedback to obtain the actual joint angle difference, and the expected rope tension is subtracted from the rope tension feedback to obtain the actual rope tension error. A PID controller is selected, and the expected trajectory of the motor angle is used as the kinematic feedforward compensation input, and then the control input is calculated based on the actual joint angle difference and the actual rope tension error. The kinematic feedforward compensation input and the calculated control input are used as the input of the force-position hybrid feedback motion controller, and the servo motor angle command is output. In some implementations, the parameters (proportional coefficient, integral coefficient, differential coefficient) of the PID controller can be debugged according to the actual situation corresponding to the model parameters.

[0123] In some implementations, the frequency domain form of the hybrid feedback control rate of the force-position hybrid feedback motion controller is as follows:

[0124]

[0125]

[0126]

[0127]

[0128] in, is the Laplace transformed variable, representing the frequency domain. , , and They are the controller outputs corresponding to the subscript numbers, i.e., the servo motor rotation angle commands. , , and The corresponding subscript numbers are The weight, , is the error corresponding to the two joint angles of the i-th joint, that is, the actual joint angle difference. , , and are the rope tension errors corresponding to the subscript numbers, i.e., the actual rope tension errors.

[0129] , , , , , , and is a preset control parameter. For different ropes, the value of the control parameter may be different. In some implementations, the positive and negative signs of the joint angle position feedback and the rope tension feedback in the above control law are determined by the arm motion and the rope retraction and extension relationship.

[0130] This application can accurately calculate the actual joint angle difference and actual rope tension error by obtaining the feedback data of the robot arm joint angle and rope tension in real time and comparing them with the expected trajectory. Based on these errors, combined with model parameters and force-position hybrid feedback motion controller, the servo motor angle command that can compensate for the current error can be determined, thereby significantly improving the motion accuracy of the robot arm.

[0131] According to other embodiments, the control effect of the control method is illustrated by combining a calculation example of a three-joint rope cluster driving a large-span spatial robot.

[0132] The task requires that the long-span space manipulator moves smoothly from the initial position to the target position. The initial position is: all joint angles are 0 degrees. Target position: all joint angles are 60 degrees (the two rotation angles corresponding to each joint angle are 30 degrees each). The initial preload of all ropes is 500N, and the expected tension of the rope on the rope-collecting side at the target position is set to 500N. Based on the above static equilibrium equation, the rope preload on the rope-releasing side corresponding to the target position is 784.4N. Based on the fifth-order polynomial method and the initial and final values ​​of the joint angles and rope tensions mentioned above, the expected joint angle trajectory and rope tension trajectory can be obtained, and the expected adjustment time is set to 5s.

[0133] For convenience, the control parameters are taken to be the same for each joint. Since the rope damping coefficient is unknown, the rope damping is ignored in the current simulation. Considering the worst case of rope oscillation, the simulation is run based on the dynamic model. Figure 5 A schematic diagram of joint simulation results provided in an embodiment of the present application, Figure 6 This is a schematic diagram of the rope tension simulation results provided in the embodiment of the present application. Figure 7 Schematic diagram of the joint angle tracking error simulation results provided in the embodiment of the present application. 5-a is used to represent the joint simulation results of the first joint, 5-b is used to represent the joint simulation results of the second joint, and 5-c is used to represent the joint simulation results of the third joint; 6-a is used to represent the rope tension simulation results of the first joint, 6-b is used to represent the rope tension simulation results of the second joint, and 6-c is used to represent the rope tension simulation results of the third joint. Reference Figure 5 , Figure 6 and Figure 7 , it can be confirmed that the robot arm can move smoothly from the initial position to the target position. For the rope tension, there will be a certain amplitude of oscillation, which will be more obvious at the joints close to the base. Figure 7 It can be seen that the maximum tracking error of each joint during the movement is less than 0.002 degrees, and the error of reaching the target position in the 5th second is less than 0.00004 degrees, which has high control accuracy.

[0134] The following describes an apparatus embodiment of the present application, which can be used to execute the method embodiment of the present application. For details not disclosed in the apparatus embodiment of the present application, reference can be made to the method embodiment of the present application.

[0135] Figure 8 This is a block diagram of a force-position hybrid control system for a rope cluster driven large-span space manipulator provided in an embodiment of the present application. Figure 8 As shown, the rope cluster driven large-span spatial manipulator force-position hybrid control system 800 includes a model building module 801, a trajectory generating module 802 and an instruction generating module 803.

[0136] The model building module 801 is used to build a kinematic model and a dynamic model of a rope cluster driven large-span space manipulator based on preset model parameters, a preset kinematic model of the manipulator body, a preset mapping relationship between rope length and joint angle, and a preset mapping relationship between motor rotation angle and rope length;

[0137] The trajectory generation module 802 is used to determine the expected trajectory of the joint angle of the robot arm and the expected trajectory of the rope tension according to the task requirements, the kinematic model and the dynamic model; and determine the expected trajectory of the motor rotation angle according to the kinematic model and the expected trajectory of the joint angle of the robot arm;

[0138] The instruction generation module 803 is used to determine the servo motor angle instruction according to the model parameters, the expected trajectory of the motor angle, the measured robot arm joint angle feedback and the measured rope tension feedback, so as to control the rope cluster to drive the large-span spatial robot to perform simulated movement according to the servo motor angle instruction.

[0139] Optionally, the model building module 801 is specifically used for:

[0140] Obtaining the mapping relationship between rope length and joint angle, the mapping relationship between motor rotation angle and rope length, the kinematic model and model parameters of the robot body; wherein the model parameters include kinematic model parameters and dynamic model parameters;

[0141] The mapping relationship between the rope length and the joint angle, the mapping relationship between the motor angle and the rope length, the kinematic model of the robot body and the kinematic model parameters are determined as a kinematic model;

[0142] The kinetic model is determined based on the Lagrangian method and the kinetic model parameters.

[0143] Optionally, the dynamic model parameters include a rope linear stiffness coefficient and a rope linear damping coefficient; the rope cluster driven large-span spatial manipulator force-position hybrid control system 800 further includes a rope tension determination module 804 for:

[0144] Based on the preset rope tension determination method, rope linear stiffness coefficient, and rope linear damping coefficient, rope tensions corresponding to each of the plurality of ropes are determined, so as to determine the dynamic model according to the rope tensions, dynamic model parameters, and the Lagrangian method.

[0145] Optionally, the rope cluster driven large-span spatial manipulator force-position hybrid control system 800 further includes a mapping relationship determination module 805, which is used to:

[0146] Based on multiple groups of preset joint-related component information corresponding to multiple joints in the rope-cluster driven large-span spatial manipulator, component data of joints, suspension rods, ropes and arm rods corresponding to each group of joint-related component information are determined;

[0147] The mapping relationship between the rope length and the joint angle is determined according to the component data of the joint, the boom, the rope and the arm and the preset mapping relationship setting method.

[0148] Optionally, the trajectory generation module 802 is specifically used to: determine the expected trajectory of the joint angle of the manipulator and the expected trajectory of the rope tension according to the task requirements, the kinematic model and the dynamic model.

[0149] According to the task requirements, determine the initial moment, end moment and preload force in the motion task corresponding to the rope cluster driving the large-span space manipulator; the preload force is the rope tension at the initial moment;

[0150] Get the joint angles at the initial and end times;

[0151] Determine the expected trajectory of the robot's joint angles based on the kinematic model and joint angles;

[0152] According to the dynamic model, determine the static equilibrium relationship;

[0153] Determine the expected tension at the end based on the static balance relationship and task requirements;

[0154] The expected trajectory of the rope tension is determined based on the kinematic model, the preload force and the expected tension at the end moment.

[0155] Optionally, when determining the expected trajectory of the motor angle according to the kinematic model and the expected trajectory of the robot arm joint angle, the trajectory generation module 802 is specifically used to:

[0156] The desired trajectory of the robot's joint angles is input into the kinematic model, and the desired trajectory of the motor angle is output.

[0157] Optionally, the instruction generation module 803 is specifically used to:

[0158] Obtain the relationship between the arm shape and rope retraction and release characteristics of the rope cluster-driven large-span space manipulator, the manipulator joint angle feedback and the rope tension feedback;

[0159] Determine the expected joint angle and expected rope tension at the current moment according to the expected trajectory of the robot arm joint angle and the expected trajectory of the rope tension;

[0160] Determine an actual joint angle difference and an actual rope tension error according to the desired joint angle, the robot arm joint angle feedback, the desired rope tension and the rope tension feedback;

[0161] The model parameters, the desired trajectory of the motor rotation angle, the actual joint angle difference and the actual rope tension error are input into the force-position hybrid feedback motion controller to output a determined servo motor rotation angle command;

[0162] The control rope cluster drives the large-span space robot to move according to the servo motor angle command.

[0163] The device performs functions similar to the method provided above. For other functions, please refer to the previous description and will not be repeated here.

[0164] Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application, such as Fig. 9 As shown, the electronic device 900 of this embodiment may include: a memory 901 and a processor 902 .

[0165] The memory 901 stores a computer program. When the computer program is executed by the processor 902, the processor 902 executes the method in the above embodiment.

[0166] The processor 902 and the memory 901 are connected, for example, via a bus.

[0167] Optionally, the electronic device 900 may further include a transceiver. It should be noted that in actual applications, the number of transceivers is not limited to one, and the structure of the electronic device 900 does not constitute a limitation on the embodiments of the present application.

[0168] The processor 902 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor 902 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0169] The bus may include a path to transmit information between the above components. The bus may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0170] The memory 901 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0171] The memory 901 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 902. The processor 902 is used to execute the application code stored in the memory 901 to implement the contents shown in the above method embodiment.

[0172] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Fig. 9 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0173] The electronic device of this embodiment can be used to execute the method of any of the above embodiments, and its implementation principle and technical effect are similar, which will not be described in detail here.

[0174] The present application also provides a non-transitory computer-readable storage medium having computer-readable instructions stored thereon. When the aforementioned instructions are executed by a processor, the processor executes the method in the above embodiment.

[0175] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a non-transient computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0176] The embodiments of the present application are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and its core idea of ​​the present application. At the same time, changes or deformations made by those skilled in the art based on the ideas of the present application, the specific implementation methods and the scope of application of the present application, all belong to the scope of protection of the present application. In summary, the content of this specification should not be construed as a limitation on the present application.

Claims

1. A force-position hybrid control method for a rope-cluster driven large-span space manipulator, characterized in that: include: Based on the preset model parameters, the preset kinematic model of the robot body, the preset mapping relationship between the rope length and the joint angle, and the preset mapping relationship between the motor angle and the rope length, the kinematic model and the dynamic model of the rope cluster driven large-span space robot are established; Determine the desired trajectory of the manipulator joint angle and the desired trajectory of the rope tension according to the task requirements, the kinematic model of the rope cluster driven large-span space manipulator and the dynamic model; determine the desired trajectory of the motor rotation angle according to the kinematic model of the rope cluster driven large-span space manipulator and the desired trajectory of the manipulator joint angle; According to the model parameters, the desired trajectory of the motor rotation angle, the desired trajectory of the robot arm joint angle, the desired trajectory of the rope tension, the measured robot arm joint angle feedback, the measured rope tension feedback and a preset force-position hybrid feedback motion controller, a servo motor rotation angle command is determined to control the rope cluster to drive the large-span spatial robot to move according to the servo motor rotation angle command; Wherein, determining the desired trajectory of the manipulator joint angle and the desired trajectory of the rope tension according to the task requirements, the kinematic model of the rope cluster driving the large-span space manipulator and the dynamic model includes: According to the task requirements, determining the initial moment, the end moment and the preload force in the motion task corresponding to the rope cluster driving the large-span space manipulator; wherein the preload force is the rope tension at the initial moment; Obtaining the joint angles at the initial moment and the end moment; Determining the expected trajectory of the joint angles of the manipulator according to the kinematic model of the rope cluster driven large-span spatial manipulator and the joint angles; According to the dynamic model, determining a static equilibrium relationship; Determining the expected tension at the end time according to the static balance relationship and the task requirements; The expected trajectory of the rope tension is determined according to the kinematic model of the rope cluster driving the large-span spatial manipulator, the preload force and the expected tension at the end moment.

2. The method according to claim 1, characterized in that The kinematic model and dynamic model of the rope cluster driven large-span space manipulator are established based on the preset model parameters, the preset kinematic model of the manipulator body, the preset mapping relationship between the rope length and the joint angle, and the preset mapping relationship between the motor angle and the rope length, including: Acquire the mapping relationship between the rope length and the joint angle, the mapping relationship between the motor rotation angle and the rope length, the kinematic model of the robot body and the model parameters; wherein the model parameters include kinematic model parameters and dynamic model parameters; Determine the kinematic model of the rope cluster driven large-span space manipulator by mapping the rope length and joint angle, mapping the motor rotation angle and rope length, the manipulator body kinematic model and kinematic model parameters; The kinetic model is determined based on the Lagrangian method and the kinetic model parameters.

3. The method according to claim 2, characterized in that The dynamic model parameters include rope linear stiffness coefficient and rope linear damping coefficient; The method further comprises: Based on a preset rope tension determination method, the rope linear stiffness coefficient, and the rope linear damping coefficient, rope tensions corresponding to each of the plurality of ropes are determined, so as to determine the dynamic model according to the rope tensions, the dynamic model parameters, and the Lagrangian method.

4. The method according to claim 1, characterized in that: Also includes: Based on multiple groups of preset joint-related component information corresponding to multiple joints in the rope-cluster driven large-span spatial manipulator, determine the component data of the joints, the suspension rods, the ropes and the arm corresponding to each group of the joint-related component information; The mapping relationship between the rope length and the joint angle is determined according to the component data of the joint, the boom, the rope and the arm and a preset mapping relationship setting method.

5. The method according to claim 1, characterized in that The method of determining the expected trajectory of the motor rotation angle according to the kinematic model of the rope cluster driven large-span space manipulator and the expected trajectory of the manipulator joint angle comprises: The desired trajectory of the robot arm joint angle is input into the kinematic model of the rope cluster driven large-span spatial robot arm, and the desired trajectory of the motor rotation angle is output.

6. The method according to claim 1, characterized in that The method of determining a servo motor rotation angle command based on the model parameters, the desired trajectory of the motor rotation angle, the desired trajectory of the robot arm joint angle, the desired trajectory of the rope tension, the measured robot arm joint angle feedback, the measured rope tension feedback and a preset force-position hybrid feedback motion controller to control the rope cluster to drive the large-span spatial robot to move according to the servo motor rotation angle command includes: Obtaining the relationship between the arm shape and the rope retraction and release characteristics of the rope cluster driven large-span space manipulator, the manipulator joint angle feedback and the rope tension feedback; Determining the expected joint angle and the expected rope tension at the current moment according to the expected trajectory of the robot arm joint angle and the expected trajectory of the rope tension; determining an actual joint angle difference and an actual rope tension error according to the desired joint angle, the robot arm joint angle feedback, the desired rope tension and the rope tension feedback; Inputting the model parameters, the desired trajectory of the motor rotation angle, the actual joint angle difference and the actual rope tension error into the force-position hybrid feedback motion controller to output the servo motor rotation angle command; The rope cluster is controlled to drive the large-span space manipulator to move according to the servo motor rotation angle instruction.

7. A feedback control system for a rope cluster driven large-span space manipulator, characterized in that: include: A model building module is used to build a kinematic model and a dynamic model of a rope cluster driven large-span space manipulator based on preset model parameters, a preset kinematic model of the manipulator body, a preset mapping relationship between rope length and joint angle, and a preset mapping relationship between motor rotation angle and rope length; A trajectory generation module is used to determine the expected trajectory of the manipulator joint angle and the expected trajectory of the rope tension according to the task requirements, the kinematic model of the rope cluster driven large-span space manipulator and the dynamic model; and determine the expected trajectory of the motor rotation angle according to the kinematic model of the rope cluster driven large-span space manipulator and the expected trajectory of the manipulator joint angle; An instruction generation module is used to determine the servo motor rotation angle instruction according to the model parameters, the expected trajectory of the motor rotation angle, the expected trajectory of the robot arm joint angle, the expected trajectory of the rope tension, the measured robot arm joint angle feedback, the measured rope tension feedback and a preset force-position hybrid feedback motion controller, so as to control the rope cluster to drive the large-span spatial robot to move according to the servo motor rotation angle instruction; The trajectory generation module is specifically used to determine the expected trajectory of the manipulator joint angle and the expected trajectory of the rope tension according to the task requirements, the kinematic model of the rope cluster driving the large-span space manipulator and the dynamic model: According to the task requirements, determining the initial moment, the end moment and the preload force in the motion task corresponding to the rope cluster driving the large-span space manipulator; wherein the preload force is the rope tension at the initial moment; Obtaining the joint angles at the initial moment and the end moment; Determining the expected trajectory of the joint angles of the manipulator according to the kinematic model of the rope cluster driven large-span spatial manipulator and the joint angles; According to the dynamic model, determining a static equilibrium relationship; Determining the expected tension at the end time according to the static balance relationship and the task requirements; The expected trajectory of the rope tension is determined according to the kinematic model of the rope cluster driving the large-span spatial manipulator, the preload force and the expected tension at the end moment.

8. An electronic device, characterized in that: include: processor; A memory storing a computer program, which, when executed by the processor, enables the processor to execute the force-position hybrid control method for a rope cluster driven large-span spatial manipulator as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium, characterized in that: Computer-readable instructions are stored thereon, and when the instructions are executed by a processor, the processor executes the force-position hybrid control method for a rope-cluster driven large-span spatial manipulator as described in any one of claims 1-6.

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