Affiliation:
1. Blavatnic School of Computer Science, Tel-Aviv University, Israel
2. Department of Computer Science, Duke University, USA
Abstract
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%.
Subject
Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modeling and Simulation,Software
Cited by
15 articles.
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