Inverse Kinematic Analysis and Simulation of the SCARA Robot Based on Recurrent Neural Networks

Abstract:
Aiming at solving complex problems of robot inverse kinematics, this paper takes SCARA robot as the research object, uses recurrent second-order neural network, and proposes a neural network solution method based on SCARA robot’s simplified forward kinematics equation and Jacobian matrix. Through the inverse kinematics analysis of the SCARA robot, the neural network model is designed and the corresponding learning algorithm is deduced. The proposed solution method is simulated and verified by MATALB software. The simulation results show that the network model can effectively solve the inverse kinematics problems of the SCARA robot, with higher solution accuracy and faster solution speed.