Analytical potential fields and control strategies for motion planning

We present a novel method for robot motion planning that constructs a network of collision free paths using a randomized search over a potential field in Configuration Space. Our method finds local minima and then connects them to form a graph, which we call a roadmap. We use a gradient search scheme to find the local minima very efficiently and accurately. To find a path between two configurations, it is then a simple matter to connect given start and goal configurations to the roadmap and to use a standard graph search algorithm to search the roadmap. The construction of the roadmap can be done in parallel with very little communication.