Rapidly exploring bur trees for optimal motion planning

摘要

This paper presents a new approach to C-space exploration and optimal path planning for robotic manipulators and planar scenarios using the structure named bur of free C-space. This structure builds upon the so-called bubble, which is a local volume of free C-space, easily computed using the distance information in the workspace. It is previously shown how burs can be used to form a rapidly exploring bur tree (RBT): a space-filling tree that resembles RRT. Now, we exploit the burs of free C-space approach to develop a new algorithm called RBT*, which is, like RRT* algorithm, provably asymptotically optimal, i.e., such that the cost of the returned solution converges almost surely to the optimum. Burs of free space offer better performance and faster convergence because it enables faster exploration of free space.