A Neural Networks-based Approach to Safe Path Planning of Mobile Robot in Unknown Environment

Abstract

For safe path planning of mobile robot in unknown environment,the paper usesa local connected Hopfield neural network(HNN)planner.The stability of the HNN isanalyzed,and the condition for the existence of the feasible path(s)is given.If a feasiblepath(s)exists,the HNN does not have any unexpected local attractive point.The connectedweight design considers both“too close”and“too far”to plan the safe path.For the HNNto on-line plan a path on a sequential processor,multi-sequential Gauss-Seidel iteration isused to accelerate the propagation of the HNN potential field.Results demonstrate that themethod has good real-time ability and adaptability to environments.