Trajectory generation for redundant manipulator using virus evolutionary genetic algorithm

Abstract

This paper deals with an application of a virus-evolutionary genetic algorithm (VEGA) to hierarchical trajectory planning of a redundant manipulator. The hierarchical trajectory planning is composed of a trajectory generator and position generator. The position generator generates collision-free intermediate positions of the redundant manipulator. The trajectory generator generates a collision-free trajectory based on some intermediate positions sent from the position generator. To generate a collision-free trajectory of the redundant manipulator, the VEGA is applied to the hierarchical trajectory planning only based on forward kinematics. The VEGA realizes horizontal propagation and vertical inheritance of genetic information in a population of candidate solutions. The main operator of the VEGA is a reverse transcription operator, which plays the roles of a crossover and selection simultaneously. In this paper, self-adaptive mutation is applied to the VEGA for local search of trajectory planning to obtain higher performance and the quick solution. Simulation results of the hierarchical trajectory planning show that the VEGA can generate a collision-free trajectory.