RRT+ : Fast Planning for High-Dimensional Configuration Spaces

Abstract

In this paper we propose a new family of RRT based algorithms, named RRT + , that are able to find faster solutions in high-dimensional configuration spaces compared to other existing RRT variants by finding paths in lower dimensional subspaces of the configuration space. The method can be easily applied to complex hyperredundant systems and can be adapted by other RRT based planners. We introduce RRT + and develop some variants, called PrioritizedRRT + , PrioritizedRRT + -Connect, and PrioritizedBidirectionalT-RRT + , that use the new sampling technique and we show that our method provides faster results than the corresponding original algorithms. Experiments using the state-of-the-art planners available in OMPL show superior performance of RRT + for high-dimensional motion planning problems.