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NEPTUNE: Nonentangling Trajectory Planning for Multiple Tethered Unmanned Vehicles

2022/12/03 by Muqing Cao, Kun Cao, Cao, Muqing +7 · 6 citations
Computer Science · Engineering · #FOS: Computer and information sciences #Optimization and Search Problems #Robotic Path Planning Algorithms #Robotics (cs.RO) #UAV Applications and Optimization

paper · pdf · doi:10.48550/arxiv.2212.01536

openalex publication_date 2022/12/03 · openalex created_date 2022/12/18 · openalex updated_date 2026/07/28

Abstract

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.

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