Maximization of Jump Height of a Serial Link Robot Based on Particle Swarm Optimization

Abstract

In this paper, we focus on the maximization of the jump height of a serial link robot. The jump height maximization problem is formulated as a nonlinear programming problem, where torque patterns to drive joints in the robot are decision variables and the objective function is an inexplicit function whose value is obtained as an output of a jump simulator. As a previous reasearch, an approximate solution method using a genetic algorithm was proposed for the jump height maximization problem. In the research, some interesting joint drive torque patterns were found by the method, but it costed much time to obtain a drive torque pattern. In order to improve the accuracy of the obtained solution and shorten the computational time, in this paper, we propose a new solution method based on particle swarm optimization (PSO) .