基于加权可通行图实现多层点云环境下的高效安全路径规划
Path Planning on Multi-level Point Cloud with a Weighted Traversability Graph
- 构建多层跳表结构简化点云地图，提升管理效率
- 通过车-点云交互直接获取局部可通行性，省去表面拟合步骤
- 在多层连通图上赋值可通行权重，支持快速搜索路径生成
本文提出一种新型路径规划方法，用于应对多层地形场景。该方法在三个方面实现创新：1）采用多层跳表结构与数据瘦身算法对点云地图进行预处理，实现地图的有序化与简化；2）通过车辆与点云的交互分析直接获取局部可通行性指数，避免了传统表面拟合工作；3）将可通行性指数分配至多层连通图中，构建加权可通行图，用于基于搜索的路径规划。对改进后的A*算法利用该图生成短且安全的路径。在室内、室外多种复杂环境中（包括多层建筑、林地、崎岖山地）的实验验证了该方法的有效性与可靠性。结果表明，该方法能有效解决地面车辆在广泛场景下的三维路径规划问题。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。