FAST ALGORITHM FOR PATH PLANNING BASED ON NEURAL NETWORK

Abstract

In this paper, the problem of global path planning is studied for a moving robot in an environment filled with obstacles whose shapes and positions are known. An aggressive algorithm for path planning is presented. The obstacles are described by an energy function defined using neural networks; different path generating equations are used, depending on whether the path points lie inside or outside the obstacles, which allows high speed of the calculations and fast convergence. The simulation results show that the computation is simple, some local minimum problems can be avoided, and the constructed path is optimal and piecewise linear.