Application of optimal algorithm in vacuum path planning of robot

摘要

In this paper, we bring forward a BP algorithm condition modeling and an attitude modeling based on PUMA robot vacuum path planning. Considering the limitation of the traditional particle swarm optimization(PSO) in searching space and easily running into local optimal points. We introduced the re-initialization mechanism based on the global information feedback to modified particle swarm optimization (MPSO) algorithm in this paper. To combine the MPSO algorithm with BP network algorithm before applying it in Vacuum Path Planning of PUMA Robot. Then the mixed BP-MPSO optimal algorithm can not only avoids the difficulty in solving the inverse motion equations, but also ensures that the optimal solution, which can obtains the global optimal aim instead of falling into local extremer. The results of simulation experiment show that this algorithm can well enhance the efficiency of vacuum path planning.