TAPE: Tether-Aware Path Planning for Autonomous Exploration of Unknown 3D Cavities Using a Tangle-Compatible Tethered Aerial Robot
This paper presents TAPE, a tether-aware path planning method for autonomous exploration of unknown 3D cavities using a tethered aerial robot. It employs a two-level hierarchical architecture with global frontier-based planning solving a TSP for distance minimization and local planning minimizing path cost and tether length via an adjustable decision function. Simulations and field tests show the method ensures tether length stays within limits in 100% of cases with only a 4.1% increase in distance traveled.
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[Submitted on 29 Jun 2026]
Title:TAPE: Tether-Aware Path Planning for Autonomous Exploration of Unknown 3D Cavities Using a Tangle-Compatible Tethered Aerial Robot
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Abstract: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.
Comments: 8 pages
Subjects:
Robotics (cs.RO)
Cite as: arXiv:2606.30817 [cs.RO]
(or arXiv:2606.30817v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2606.30817
arXiv-issued DOI via DataCite (pending registration)
Journal reference: IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 10550-10557, 2022
Related DOI:
https://doi.org/10.1109/LRA.2022.3194691
DOI(s) linking to related resources
Submission history
From: Louis Petit [view email] [v1] Mon, 29 Jun 2026 18:44:56 UTC (5,469 KB)
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