Optimal sampling-based motion planning under differential constraints: The driftless case
Optimal sampling-based motion planning under differential constraints: The driftless case
Motion planning under differential constraints is a classic problem in robotics. To date, the state of the art is represented by sampling-based techniques, with the Rapidly-exploring Random Tree algorithm as a leading example. Yet, the problem is still open in many aspects, including guarantees on the quality of the obtained …