Repetitive movement planning method for redundancy mechanical arm

Abstract

The invention discloses a repetitive movement planning method for a redundancy mechanical arm based on a variable-parameter convergence differential neural network. The repetitive movement planning method includes the following steps that firstly, a redundancy mechanical arm inverse kinematics equation is established on a speed layer through the track of the tail end of the redundancy mechanical arm; secondly, the inverse kinematics problem in the first step is designed as a time-varying convex quadratic programming problem constrained by the equation; thirdly, a repetitive movement index is introduced in the time-varying convex quadratic programming problem; fourthly, the time-varying convex quadratic programming problem in which the repetitive movement index is introduced is converted into a time-varying matrix equation through a lagrangian function; fifthly, the time-varying matrix equation is solved through the variable-parameter convergence differential neural network; and sixthly, integration is conducted on the optimal solution, obtained in the fifth step, on the speed layer of the redundancy mechanical arm, and the optimal solution of the joint angle is obtained. By means of the repetitive movement planning method for the redundancy mechanical arm based on the variable-parameter convergence differential neural network, the variable-parameter convergence differential neural network is adopted for solving the repetitive movement of the redundancy mechanical arm, and the beneficial effects of the high calculating efficiency, high real-time performance and good robustness are achieved.

Description

technical field [0001] The invention relates to the field of redundant manipulators, in particular to a repetitive motion planning method for redundant manipulators based on variable parameter convergence differential neural networks. Background technique [0002] Redundant manipulator means that the number of degrees of freedom of the manipulator is more than the number of degrees of freedom necessary to complete the task. Due to more degrees of freedom, the redundant manipulator can also complete the main task of the end effector, such as avoiding obstacles. Additional tasks such as objects, shutdown limit positions, and strange states of the robotic arm. Repetitive motion means that after the end of the mechanical arm completes a cycle of motion, all its joints can return to the initial position, not just the end of the mechanical arm returns to the initial position. In automated industrial production, the robotic arm is usually required to perform batch production activ...

AI Technical Summary

Problems solved by technology

[0003] The traditional solution to the inverse kinematics problem of redundant manipulators is based on the pseudo-inverse method. This method has a large amount of calculation, poor real-time performance, and single problem constraints, which are greatly restricted in the application of actual manipulators.

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