GPAC enables drone swarms to transport cable-suspended payloads without central coordination

GPAC is a decentralized control architecture for multi-quadrotor cable-suspended payload transport. It operates on the full nonlinear configuration manifold, integrating 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. The key innovation is implicit coordination: each quadrotor independently estimates its effective load share from local cable measurements, so combined forces converge to the correct total without knowledge of the number of drones or payload mass. Inter-agent communication is limited to a low-rate neighbor-position broadcast for collision avoidance, ensuring scalability and robustness.

The system was validated in high-fidelity simulations with flexible cables, onboard sensor fusion, and wind turbulence, with all control and estimation loops closed through the estimator. Results show a mean payload-tracking RMSE of 33.8 cm (2.8% coefficient of variation over 13 seeds) at low per-agent computational cost. The safety filter reduces operational risk with input-to-state safety (ISSf) margins that hold exactly under single-constraint activation. Additionally, the concurrent learning-based mass estimator eliminates the need for persistent excitation, a practical advantage for real-world deployment. The paper is accepted for presentation at the IEEE/RSJ IROS 2026 conference.