NEPTUNE: Nonentangling Trajectory Planning for Multiple Tethered Unmanned Vehicles
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Abstract (arXiv)
Despite recent progress on trajectory planning of multiple robots and path planning of a single tethered robot, planning of multiple tethered robots to reach their individual targets without entanglements remains a challenging problem. In this paper, we present a complete approach to address this problem. Firstly, we propose a multi-robot tether-aware representation of homotopy, using which we can efficiently evaluate the feasibility and safety of a potential path in terms of (1) the cable length required to reach a target following the path, and (2) the risk of entanglements with the cables of other robots. Then, the proposed representation is applied in a decentralized and online planning framework that includes a graph-based kinodynamic trajectory finder and an optimization-based trajectory refinement, to generate entanglement-free, collision-free and dynamically feasible trajectories. The efficiency of the proposed homotopy representation is compared against existing single and multiple tethered robot planning approaches. Simulations with up to 8 UAVs show the effectiveness of the approach in entanglement prevention and its real-time capabilities. Flight experiments using 3 tethered UAVs verify the practicality of the presented approach.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Dec 2022.
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Citing papers per year: 2024: 2; 2025: 1; 2026: 1.
4 papers.
- 2025UAVScenes: A Multi-Modal Dataset for UAVscited by 27
- 2024MMAUD: A Comprehensive Multi-Modal Anti-UAV Dataset for Modern Miniature Drone Threatscited by 18
- 2024TAME: Temporal Audio-based Mamba for Enhanced Drone Trajectory Estimation and Classificationcited by 2
- 2026Coverage Path Planning: Classical Foundations, Recent Advances, and Future Directionscited by 0
- 2026Coverage Path Planning: Classical Foundations, Recent Advances, and Future Directions12 Jul 2026
- 2025UAVScenes: A Multi-Modal Dataset for UAVs30 Jul 2025
- 2024TAME: Temporal Audio-based Mamba for Enhanced Drone Trajectory Estimation and Classification17 Dec 2024
- 2024MMAUD: A Comprehensive Multi-Modal Anti-UAV Dataset for Modern Miniature Drone Threats6 Feb 2024