Trajectory planning of cellular manipulator system using virus-evolutionary genetic algorithm

Abstract

This paper deals with an application of a genetic algorithm based on a virus theory of evolution (VEGA) to trajectory planning of a cellular manipulator system. A cellular manipulator system is composed of a large number of autonomous parts and tools. The form of the cellular manipulator system is dynamically reconfigured according to its environment and given tasks. In this paper, the VEGA is applied to a trajectory planning problem. The VEGA realizes a horizontal propagation and a vertical inheritance of genetic information in a population. The main operator of the VEGA is a reverse transcription operator, which plays the roles of a crossover and a selection at the same time. Simulation results of trajectory planning shows that the VEGA generates a collision-free trajectory.