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A Framework for Guided Motion Planning
Randomized sampling based algorithms are widely used in robot motion planning due to the problem's intractability, and are experimentally effective on a wide range of problem instances.
Evaluating Guiding Spaces for Motion Planning
Randomized sampling based algorithms are widely used in robot motion planning due to the problem's intractability, and are experimentally effective on a wide range of problem instances.
Scalable Multi-robot Motion Planning for Congested Environments With Topological Guidance
Multi-robot motion planning (MRMP) is the problem of finding collision-free paths for a set of robots in a continuous state space.
Hypergraph-based Multi-Robot Task and Motion Planning
We present a multi-robot task and motion planning method that, when applied to the rearrangement of objects by manipulators, results in solution times up to three orders of magnitude faster than existing methods and successfully plans for problems with up to twenty objects, more than three times as many objects as comparable methods.
