Neural maps for mobile robot navigation

Abstract

Neural maps have been recently proposed as an alternative method for mobile robot path planning. However, these proposals are mostly theoretical and primarily concerned with biological plausibility. This paper addresses the applicability of neural maps to mobile robot navigation with focus on efficient implementations It is suggested that neural maps offer a promising alternative compared to the traditional distance transform and harmonic function methods. Applications of neural maps are presented for both global and local navigation. Experimental results (both simulated and real-world on a Nomad 200 mobile robot) demonstrate the validity of the approach. Our work reveals that a key issue for success of the method is the organization of the map that needs to be optimized for the situation at hand.