Further Study of Robot Path Planning Algorithm Based on Artificial Immune Net Theory

摘要

Based on the artificial immune net theory, the moving robot path finding and planning algorithm is perfected in the paper. The design ideas and the detail programs are depicted. The convergence of the algorithm was proven by the Markov-Chain. The experiments comparing with the gravitation algorithm, the artificial neural networks and the gene algorithm have been done. It shows that the algorithm has very nice flexibility, is suitable for the different planning conditions, solutes the cheat problem and reveals its higher intelligence.