English

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

Robotics 2023-07-12 v2

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.

Cite

@article{arxiv.2206.14071,
  title  = {R2: Heuristic Bug-Based Any-angle Path-Planning using Lazy Searches},
  author = {Yan Kai Lai and Prahlad Vadakkepat and Abdullah Al Mamun and Cheng Xiang and Tong Heng Lee},
  journal= {arXiv preprint arXiv:2206.14071},
  year   = {2023}
}

Comments

Rejected, and replaced with new prototype with same name

R2 v1 2026-06-24T12:07:06.554Z