Abstract: A method is presented for programming a repeating motion of a redundant robotic arm on the basis of a variable parameter convergence differential neural network. The method may include establishing an inverse kinematics equation, creating an inverse kinematics problem, introducing a repeating motion indicator, converting a time-varying convex quadratic programming problem into a time-varying matrix equation, and integrating an optimal solution to obtain an optimal solution of a joint angle. The use of the variable parameter convergence differential neural network to solve the repeating redundant mechanical motion has the advantages of high computational efficiency, high real-time performance, and enhanced robot arm robustness.

Abstract: A method is presented for programming a repeating motion of a redundant robotic arm on the basis of a variable parameter convergence differential neural network. The method may include establishing an inverse kinematics equation, creating an inverse kinematics problem, introducing a repeating motion indicator, converting a time-varying convex quadratic programming problem into a time-varying matrix equation, and integrating an optimal solution to obtain an optimal solution of a joint angle. The use of the variable parameter convergence differential neural network to solve the repeating redundant mechanical motion has the advantages of high computational efficiency, high real-time performance, and enhanced robot arm robustness.