Euclidean Distance-Optimal Post-Processing of Grid-Based Paths

05/09/2021 ∙ by Guru Koushik Senthil Kumar, et al. ∙ 0

Paths planned over grids can often be suboptimal in an Euclidean space and contain a large number of unnecessary turns. Consequently, researchers have looked into post-processing techniques to improve the paths after they are planned. In this paper, we propose a novel post-processing technique, called Homotopic Visibility Graph Planning (HVG) which differentiates itself from existing post-processing methods in that it is guaranteed to shorten the path such that it is at least as short as the provably shortest path that lies within the same topological class as the initially computed path. We propose the algorithm, provide proofs and compare it experimentally against other post-processing methods and any-angle planning algorithms.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 3

page 4

page 5

page 6

page 7

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.