Aidman, E.Ivancevic, V.Jennings, A.2009-11-232009-11-232008International Journal of Intelligent Defence Support Systems, 2008; 1(2):93-1151755-15871755-1595http://hdl.handle.net/2440/53634Copyright © 2008 Inderscience Enterprises Limited. All rights reserved.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 crossingenreaction-diffusion systemscoupled activator-inhibitor fieldsdynamical gridrobot navigationcrowded environmentslocal activationgeneralised inhibitionneural field equationsneural attractor dynamicsautonomous vehiclespedestrian crossingmobile robotsneural networksJournal article002008491210.1504/IJIDSS.2008.02196940440