The International Journal of Robotics Research · 2014 · 24 citations · 31 references
ComputingComputer ScienceAlgorithmsMotion PlanningPath PlanningGraph AlgorithmsGraph SimplificationNetwork Flow AlgorithmsRoadmap PlanningRobot Motion PlanningShortest Path AlgorithmsAverage Path LengthGraph RelaxationRoadmap SparsificationShortest Path LengthShortest Path OptimizationShortest Path PlanningShortest Path ProblemsSparse Roadmaps
Roadmaps constructed by the recently introduced PRM* algorithm for asymptotically-optimal motion planning encode high-quality paths yet can be extremely dense. We consider the problem of [Formula: see text] the roadmap, i.e. reducing its size, while minimizing the degradation of the quality of paths that can be extracted from the resulting roadmap. We present a simple, effective sparsifying algorithm, called [Formula: see text][Formula: see text] (RSEC). The primitive operation used by RSEC is [Formula: see text]—the contraction of a roadmap edge ( v′, v″) to a new vertex [Formula: see text] and the connection of the new vertex [Formula: see text] to the neighboring vertices of the contracted edge’s vertices (i.e. to all neighbors of [Formula: see text] and [Formula: see text]). For certain scenarios, we compress more than 97% of the edges and vertices of a given roadmap at the cost of degradation of average shortest path length by at most 4%.
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Surface simplification using quadric error metrics
Michael Garland, Paul S. Heckbert · 1997 · 3.4K citations
The Open Motion Planning Library
Ioan A. Şucan, Mark Moll, Lydia E. Kavraki · IEEE Robotics & Automation Magazine · 2012 · 1.6K citations
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