Forward Kinematics Solution of Cable Robot based on Neural Network and L-M Algorithm

Abstract

Cable-driven parallel robots (CDPRs) have been applied very well because of its advantages. Like other parallel robots, the forward kinematic solution of the parallel robot driven by cable is usually faced with complex nonlinear equations, and its solution is always a difficult problem. The traditional numerical iteration method is heavily dependent on the selection of initial values, which is easy to fall into local convergence, leading to the result of calculation is not necessarily the ideal spatial pose. The neural network has good nonlinear fitting ability and can give correct spatial pose, but the solution accuracy needs to be improved. The convergence and precision of the forward kinematic solution of the CDPRs is solved by the improved algorithm combining neural network and Levenberg- Marquardt algorithm.