Decentralized Geometric Control for Cable-Suspended Payload Transport with Adaptive Mass Estimation
This paper presents GPAC, a four-layer decentralized control architecture for multiple quadrotors transporting a cable-suspended payload without central coordination or explicit communication of cable states. Each quadrotor independently estimates its load share from local measurements, enabling implicit coordination. The system integrates geometric control, anti-swing regulation, wind rejection, adaptive mass estimation via concurrent learning, and a priority-ordered safety filter based on control barrier functions. High-fidelity simulations demonstrate a mean tracking RMSE of 33.8 cm with low computational cost.
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[Submitted on 20 Jun 2026]
Title:Decentralized Geometric Control for Cable-Suspended Payload Transport with Adaptive Mass Estimation
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Abstract:Cooperative aerial transport requires controllers that respect nonlinear manifold geometry, operate without centralized coordination, and respect operational safety constraints. To address these demands, we present GPAC, a four-layer hierarchical architecture that enables $N$ quadrotors to transport a cable-suspended payload without a central coordinator or by exchanging cable states or adaptive parameters. The key insight is implicit coordination: each quadrotor independently estimates its effective load share from local cable measurements, so combined forces converge to the correct total, even without knowledge of $N$ or the payload mass; the payload position is reconstructed locally from each agent's own cable geometry, and the only inter-agent communication is a low-rate neighbor-position broadcast for collision avoidance. GPAC operates directly on the full nonlinear configuration manifold and integrates geometric position and attitude control, anti-swing regulation, an extended-state observer for wind rejection, concurrent learning-based mass estimation without persistent excitation, and a priority-ordered control barrier function (CBF)-inspired safety filter that reduces operational risk, with input-to-state safety (ISSf) margins that hold exactly under single-constraint activation. A compatibility result shows that the filter's force modifications keep the desired attitude within the almost-global stability region of the $\mathrm{SO}(3)$ attitude controller. Finally, high-fidelity simulation with flexible cables, onboard sensor fusion, and wind turbulence -- with all control and estimation loops closed through the estimator -- yields a mean payload-tracking RMSE of 33.8 cm (2.8\% coefficient of variation over 13 seeds) at a low per-agent computational cost.
Comments: Accepted to be presented at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2026
Subjects:
Robotics (cs.RO); Multiagent Systems (cs.MA); Systems and Control (eess.SY)
Cite as: arXiv:2607.00024 [cs.RO]
(or arXiv:2607.00024v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2607.00024
arXiv-issued DOI via DataCite
Submission history
From: Hadi Hajieghrary [view email] [v1] Sat, 20 Jun 2026 15:33:17 UTC (3,090 KB)
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