Solution for Forward Kinematics of 6-DOF Parallel Robot Based on Particle Swarm Optimization

Abstract

The analysis of the forward kinematics is the foundation for studying other performances of the parallel robot. Making use of the property that it is easy to obtain the inverse kinematics of 6-DOF parallel robot, the forward kinematics of the 6-DOF parallel robot is transformed by using inverse kinematics results through training and learning. The nonlinear mapping from the joint variable space to the operation variable space for the platform is accomplished solving the location and posture. The BP neural network is used to solve the forward kinematics, and the particle swarm optimization is applied to train the neural network. Simulation results show that this approach can be used for the online control of parallel robot with faster computing speed and more accurate solution.