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Nonlinear MPC for Full-Pose Manipulation of a Cable-Suspended Load using Multiple UAVs

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arxiv 2301.08545 v4 pith:JUNHNWGP submitted 2023-01-20 cs.RO

classification cs.RO
keywords uavscablescontrolmethodmultiplenonlinearaccountalgorithm
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In this work, we propose a centralized control method based on nonlinear model predictive control to let multiple UAVs manipulate the full pose of an object via cables. At the best of the authors knowledge this is the first method that takes into account the full nonlinear model of the load-UAV system, and ensures all the feasibility constraints concerning the UAV maximumum and minimum thrusts, the collision avoidance between the UAVs, cables and load, and the tautness and maximum tension of the cables. By taking into account the above factors, the proposed control algorithm can fully exploit the performance of UAVs and facilitate the speed of operation. Simulations are conducted to validate the algorithm to achieve fast and safe manipulation of the pose of a rigid-body payload using multiple UAVs. We demonstrate that the computational time of the proposed method is sufficiently small (<100 ms) for UAV teams composed by up to 10 units, which makes it suitable for a huge variety of future industrial applications, such as autonomous building construction and heavy-load transportation.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. CrazyMARL: Decentralized Direct Motor Control Policies for Cooperative Aerial Transport of Cable-Suspended Payloads

    cs.RO 2025-09 conditional novelty 6.0 of 10

    A decentralized reinforcement learning controller with direct motor commands lets teams of drones carry cable-suspended payloads, recover from harsh disturbances, and transfer from simulation to real Crazyflie hardware.

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