让带缆无人机在未知洞穴中自动探索，兼顾路径短和缆绳不缠绕。
TAPE: Tether-Aware Path Planning for Autonomous Exploration of Unknown 3D Cavities Using a Tangle-Compatible Tethered Aerial Robot
- 分两级规划：全局解旅行商问题减路径，局部调权衡减少缆绳长度。
- 仿真中路径增4.1%但缆绳未超限比例从100%降至53%，加本地规划后达100%。
- 适合需带缆作业的复杂洞穴探测场景，如地质勘察或救援搜索。
本文提出首个针对未知三维洞穴的自主探索方法TAPE，旨在最小化行进距离与释放的缆绳长度。鉴于缆绳缠绕受全局路径影响较小，该方法采用两级分层架构：全局基于前哨点规划求解旅行商问题（TSP）以缩短距离；局部规划则通过可调节决策函数，在路径代价与缆绳长度间权衡优化。所提方法在详细仿真与实地测试中评估。平均而言，相比无局部规划的TSP方案，路径长度增加4.1%，但在53%的仿真案例中缆绳超过最大允许值；而加入本方法后，该比例提升至100%达标。
原文摘要 · Abstract (English)
This letter presents the first method for autonomous exploration of unknown cavities in three dimensions (3D) that focuses on minimizing the distance traveled and the length of tether unwound. Considering that the tether entanglements are little influenced by the global path, our approach employs a 2-level hierarchical architecture. The global frontier-based planning solves a Traveling Salesman Problem (TSP) to minimize the distance. The local planning attempts to minimize the path cost and the tether length using an adjustable decision function whose parameters play on the trade-off between these two values. The proposed method, TAPE, is evaluated through detailed simulation studies as well as field tests. On average, our method generates a 4.1% increase in distance traveled compared to the TSP solution without our local planner, with which the length of the tether remains below the maximum allowed value in 53% of the simulated cases against 100% with our method.
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