Mobile Robot Path Planning Base on the Hybrid Genetic Algorithm in Unknown Environment

This paper presents an unknown environment robot path planning algorithm. The robot working environments are expressed by grid model; Using digital potential field generated initial path population, and its optimization find the shortest path, and individual evaluation function were processed fitness function both feasible path and unfeasible path fitness function, and then by increasing the deleted and inserted operators to meet the requirement of avoiding obstacles in the path planning. By designing algorithm and experimentations on Pioneer III mobile robot, we can see that when we do the dynamic mobile robot path planning with this method, there are no obstacles of any collision; The planning path is short and smooth curves, to the satisfaction of the effect of planning and convergence rate.