A Feedforward Torque Compensation Method for Robot
A compensation method and robot technology, applied in manipulators, program-controlled manipulators, manufacturing tools, etc., can solve the problems of low precision, high operator requirements, difficult to obtain accurately, etc., and achieve the effect of high precision
Active Publication Date: 2021-07-23
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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Problems solved by technology
However, in practice, the dynamic model of the robot is difficult to obtain accurately, and the compensation effect will be poor by directly using the theoretically calculated parameters to establish the dynamic model.
In addition, robot kinematics and dynamics data are continuously related in time, and the memory characteristics of friction force and motor parameters bring time-varying characteristics with temperature changes. Traditional dynamic parameter identification methods cannot compensate for these factors.
[0004] In short, the traditional robot feed-forward torque compensation method and the calculation method of theoretical parameters have very low accuracy, or need to design complex experiments to determine the mechanical model of the robot for a specific type of robot, and the experimental process has high requirements for operators.
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[0030] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangements of components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.
[0031] The following description of at least one exemplary embodiment is merely illustrative in nature and in no way taken as limiting the invention, its application or uses.
[0032] Techniques, methods and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such techniques, methods and devices should be considered part of the description.
[0033] In all examples shown and discussed herein, any specific values should be construed as exemplary only, and not as limitations. Therefore, other instances of the exemplary embodiment may have dif...
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The invention discloses a robot feedforward torque compensation method. The method includes: inputting the state information of the robot at the current moment into the trained cyclic neural network model, and outputting the predicted torque at the subsequent time point, wherein the training set of the cyclic neural network model represents the state information of the robot and is based on the dynamics model The corresponding relationship between the calculated predicted torques, the robot state information reflects the motion trajectories of multiple joint time series. The invention can obtain more accurate feed-forward torque compensation, and is applicable to robots of different models.
Description
technical field [0001] The present invention relates to the technical field of robot control, and more particularly, relates to a robot feedforward torque compensation method. Background technique [0002] With its safety, flexibility and easy-to-use features, collaborative robots, as an important supplement to traditional industrial robots, have huge growth potential in both industrial and non-industrial fields. [0003] For the sake of safety, collaborative robots generally have low stiffness. In order to improve the motion accuracy of the robot and reduce the vibration caused by motion, more attention needs to be paid to the dynamic effect of the robot body. When traditional robots deal with dynamic effects, they often counteract the disturbance caused by dynamic effects by increasing the closed-loop stiffness of the robot joint control system. But too much gain may cause instability and shock. In theory, if the dynamic model of the robot can be accurately obtained, the...
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IPC IPC(8): B25J9/16
CPCB25J9/163B25J9/1633
Inventor 冯伟吴新宇梁济民侯至丞刁思勉王卫军
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI