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R2: Heuristic Bug-Based Any-angle Path-Planning using Lazy Searches

2022-06-28 15:14:42
Yan Kai Lai, Prahlad Vadakkepat, Abdullah Al Mamun, Cheng Xiang, Tong Heng Lee

Abstract

R2 is a novel online any-angle path planner that uses heuristic bug-based or ray casting approaches to find optimal paths in 2D maps with non-convex, polygonal obstacles. R2 is competitive to traditional free-space planners, finding paths quickly if queries have direct line-of-sight. On large sparse maps with few obstacle contours, which are likely to occur in practice, R2 outperforms free-space planners, and can be much faster than state-of-the-art free-space expansion planner Anya. On maps with many contours, Anya performs faster than R2. R2 is built on RayScan, introducing lazy-searches and a source-pledge counter to find successors optimistically on contiguous contours. The novel approach bypasses most successors on jagged contours to reduce expensive line-of-sight checks, therefore requiring no pre-processing to be a competitive online any-angle planner.

Abstract (translated)

URL

https://arxiv.org/abs/2206.14071

PDF

https://arxiv.org/pdf/2206.14071.pdf


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