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- W2024392402 abstract "SUMMARY A crucial part of probabilistic roadmap planners is the nearest neighbor search, which is typically done by exact methods. Unfortunately, searching the neighbors can become a major bottleneck for the performance. This can occur when the roadmap size grows especially in high-dimensional spaces. In this paper, we investigate how well the approximate nearest neighbor searching works with probabilistic roadmap planners. We propose a method that is based on the locality-sensitive hashing and show that it can speed up the construction of the roadmap considerably without reducing the quality of the produced roadmap." @default.
- W2024392402 created "2016-06-24" @default.
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- W2024392402 date "2014-04-09" @default.
- W2024392402 modified "2023-10-14" @default.
- W2024392402 title "Speeding up probabilistic roadmap planners with locality-sensitive hashing" @default.
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- W2024392402 doi "https://doi.org/10.1017/s0263574714000873" @default.
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