Robot Navigation with a Polar Neural Map

Neural maps have been recently proposed as an alternative method for mobile robot path planning (Glasius, Komoda, and Gielen 1995). However, these proposals are mostly theoretical and are primarily concerned with biological plausibility. Our purpose is to investigate their applicability on real robots. Information about the environment is mapped on a topologically ordered neural population. The diffusion dynamics force the network into a unique equilibrium state that defines the navigation landscape for the given target. A path from any initial position to the target (corresponding to the peak of the activation surface) is derived by a steepest ascent procedure. The figures below show an example on a 50 x 50 rectangular map (a. Environment, b. Contours of activation, c. Path).