3 research outputs found
NEPTUNE: Non-Entangling Planning for Multiple Tethered Unmanned Vehicles
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.Comment: Accepted for publication in IEEE Transaction on Robotic