This paper presents some of the recent improvements in sampling-based robot motion planning. Emphasis is placed on work that brings motion-planning algorithms closer to applicability in real environments. Methods that approach increasingly difficult motion-planning problems including kinodynamic motion planning and dynamic environments are discussed. The ultimate goal for such methods is to generate plans that can be executed with few modifications in a real robotics mobile platform.
['Konstantinos I. Tsianos', 'Ioan Alexandru Sucan', 'Lydia E. Kavraki']
Research paper: Sampling-based robot motion planning: Towards realistic applications