A coupled reaction-diffusion field model for perception-action cycle with applications to robot navigation

Abstract

A generalised reaction-diffusion field model for robot navigation is proposed. It utilises two mutually antagonistic neural fields counteracting in patterns similar to that of flexor/extensor muscles controlling the movements in major joints in the human body. Combining local activation and generalised inhibition represented by Amari's neural field equations and extended by the Fitzhugh-Nagumo and Wilson-Cowan activator-inhibitor systems, results in the type of neural attractor dynamics that may lead to spontaneous oscillatory pattern formation. Preliminary simulation data suggest that this approach has utility in enabling a team of autonomous vehicles to navigate in a crowded pedestrian crossing