Efficient C-space modelling using Kohonen maps

Abstract

Global path planning for robot manipulators is a main topic in robot motion planning. Path planners using an explicit configuration-space (C-space) representation demonstrate resolution completeness. Keeping the C-space resolution reasonable with growing number of degrees of freedom (DOF) of a robot is a challenging problem, since the C-space grows exponentially with the number of DOF. The approach presented leads to a high resolution representation of collision-free C-space regions and a low one of colliding C-space regions. This C-space representation by a non-equidistant C-space grid is achieved by using Kohonen's self organizing feature maps. The effectiveness of the approach is demonstrated by examples of up to 5-dimensional C-spaces used by a path planner.