Oscillatory Neural Fields for Globally Optimal Path Planning
Michael D. Lemmon · 1991
A neural network solution is proposed for solving path planning problems faced by mobile robots. The proposed network is a two-dimensional sheet of neurons forming a distributed representation of the robot's workspace. Lateral interconnections between neurons are "cooperative", so that the network exhibits oscillatory behaviour. These oscillations are used to gen-erate solutions of Bellman's dynamic programming equation in the context of path planning. Simulation experiments imply that these networks locate global optimal paths even in the presence of substantial levels of circuit nOlse. 1 Dynamic Programming and Path Planning Consider a 2-DOF robot moving about in a 2-dimensional world. A robot's location is denoted by the real vector, p. The collection of all locations forms a set called the workspace. An admissible point in the workspace is any location which the robot may occupy. The set of all admissible points is called the free workspace. The