Path Planning on Multi-level Point Cloud with a Weighted Traversability Graph

Fuente: arXiv
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Main Authors: Tang, Yujie, Li, Quan, Geng, Hao, Xie, Yangmin, Shi, Hang, Yang, Yusheng
Format: Preprint
Published: 2025
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author Tang, Yujie
Li, Quan
Geng, Hao
Xie, Yangmin
Shi, Hang
Yang, Yusheng
author_facet Tang, Yujie
Li, Quan
Geng, Hao
Xie, Yangmin
Shi, Hang
Yang, Yusheng
contents This article proposes a new path planning method for addressing multi-level terrain situations. The proposed method includes innovations in three aspects: 1) the pre-processing of point cloud maps with a multi-level skip-list structure and data-slimming algorithm for well-organized and simplified map formalization and management, 2) the direct acquisition of local traversability indexes through vehicle and point cloud interaction analysis, which saves work in surface fitting, and 3) the assignment of traversability indexes on a multi-level connectivity graph to generate a weighted traversability graph for generally search-based path planning. The A* algorithm is modified to utilize the traversability graph to generate a short and safe path. The effectiveness and reliability of the proposed method are verified through indoor and outdoor experiments conducted in various environments, including multi-floor buildings, woodland, and rugged mountainous regions. The results demonstrate that the proposed method can properly address 3D path planning problems for ground vehicles in a wide range of situations.
format Preprint
id arxiv_https___arxiv_org_abs_2504_21622
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Path Planning on Multi-level Point Cloud with a Weighted Traversability Graph
Tang, Yujie
Li, Quan
Geng, Hao
Xie, Yangmin
Shi, Hang
Yang, Yusheng
Robotics
This article proposes a new path planning method for addressing multi-level terrain situations. The proposed method includes innovations in three aspects: 1) the pre-processing of point cloud maps with a multi-level skip-list structure and data-slimming algorithm for well-organized and simplified map formalization and management, 2) the direct acquisition of local traversability indexes through vehicle and point cloud interaction analysis, which saves work in surface fitting, and 3) the assignment of traversability indexes on a multi-level connectivity graph to generate a weighted traversability graph for generally search-based path planning. The A* algorithm is modified to utilize the traversability graph to generate a short and safe path. The effectiveness and reliability of the proposed method are verified through indoor and outdoor experiments conducted in various environments, including multi-floor buildings, woodland, and rugged mountainous regions. The results demonstrate that the proposed method can properly address 3D path planning problems for ground vehicles in a wide range of situations.
title Path Planning on Multi-level Point Cloud with a Weighted Traversability Graph
topic Robotics
url https://arxiv.org/abs/2504.21622