Nonholonomic, Bounded Curvature Path Planning In Cluttered Environments

The problem of planning a path for a robot vehicle amidst obstacles is considered in the present work. A method that attempts at extending Reeds and Shepp's results on shortest paths of bounded curvature in absence of obstacles to the case where obstacles are present in the workspace. Successful outcomes of the proposed techniques are paths consisting of a simple composition of Reeds/Shepp paths that solves the problem. For a particular vehicle shape, the path provided by the method, if regular, is also the shortest feasible path. However, in its original version, the method may fail to find a path. This limitation can be overcome using a few simple heuristics. Applications to both unicycle and car-like mobile robots of generated shape are described and their performance and practicality discussed