Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Relevant Region Exploration On General Cost-maps For Sampling-Based
  Motion Planning   Asymptotically optimal sampling-based planners require an intelligent
exploration strategy to accelerate convergence. After an initial solution is
found, a necessary condition for improvement is to generate new samples in the
so-called "Informed Set". However, Informed Sampling can be ineffective in
focusing search if the chosen heuristic fails to provide a good estimate of the
solution cost. This work proposes an algorithm to sample the "Relevant Region"
instead, which is a subset of the Informed Set. The Relevant Region utilizes
cost-to-come information from the planner's tree structure, reduces dependence
on the heuristic, and further focuses the search. Benchmarking tests in uniform
and general cost-space settings demonstrate the efficacy of Relevant Region
sampling.

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The categories of this paper are: gr-qc
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The categories of this paper are: hep-th
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The categories of this paper are: hep-lat
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The categories of this paper are: q-fin
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The categories of this paper are: cmp-lg
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The categories of this paper are: solv-int
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The categories of this paper are: alg-geom
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The categories of this paper are: econ
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The categories of this paper are: q-bio
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The categories of this paper are: nucl-th
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The categories of this paper are: cond-mat
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The categories of this paper are: comp-gas
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The categories of this paper are: dg-ga
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The categories of this paper are: hep-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: physics