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— We present a general search strategy called SAN-DROS for motion planning, and its applications to motion planning for three types of robots: 1) manipulator; 2) rigid object; 3) multiple rigid objects. SANDROS is a dynamic-graph search algorithm, and can be described as a hierarchical, nonuniform-multiresolution, and best-first search to find a(More)
To address the need for a fast path planner, we present a learning algorithm that improves path planning by using past experience to enhance future performance. The algorithm relies on an existing path planner to provide solutions to difficult tasks. From these solutions, an evolving sparse network of useful robot configurations is learned to support faster(More)
In this paper, we present a new hybrid motion planner that is capable of exploiting previous planning episodes when confronted with new planning problems. Our approach is applicable when several (similar) problems are successively posed for the same static environment, or when the environment changes incrementally between planning episodes. At the heart of(More)