Single-query, Bi-directional, Lazy roadmap planner applied to car-like robots

The Single-query, Bi-directional, Lazy roadmap (SBL) algorithm successfully builds upon the traditional Probabilistic Roadmaps (PRM) approach by introducing a number of related optimizations. While these optimizations are applicable in the domain of car-like robots, the non-holonomic constraints of these systems and non-independence of several of their degrees of freedom pose challenges that will be examined in this paper. We present several enhancements that improve the quality of the generated path in comparison with the simple adaptation of the SBL algorithm. Results demonstrate that this work provides a planner that quickly and reliably discovers efficient paths for car-like robots.