Robot Path Planning Based on Cellular Automata with Mixed Neighborhoods
Haochen Pei, Yuansheng Lou, Feng Ye · 2018
In order to solve the problem of infeasible path obtained by cellular automata (CA) with Moore neighborhood more effectively, the cellular automata with mixed neighborhoods is proposed for robot path planning. All the problem areas are found by the problem area recognition formula, and all the free cells in these areas adopt the Von Neumann neighborhood, and the free cells in other areas adopt the Moore neighborhood. According to neighborhood type, the free cells are evolved from the goal position to the start position by the transition rule, and then search from the start position to the goal position. The simulation results show that the proposed method is effective.