Trajectory planning of reconfigurable redundant manipulator using virus-evolutionary genetic algorithm

This paper deals with an application of a virus-evolutionary genetic algorithm (VEGA) to trajectory planning of a reconfigurable redundant manipulator. The form of the reconfigurable redundant manipulator is dynamically reconfigured according to its environment and given tasks. In this paper, the VEGA is applied to a trajectory planning 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 a selection simultaneously. Simulation results of trajectory planning show that the VEGA can generate a collision-free trajectory