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This paper presents a sensorless state estimation and control framework for quadrotors transporting cable-suspended payloads, addressing limitations of prior work that relies on direct load measurements. They use the Udwadia-Kalaba method to explicitly incorporate cable geometric constraints into the dynamic model, enabling consistent derivation of tension force for NMPC. Real-robot experiments demonstrate that explicitly modeling load dynamics reduces trajectory-tracking errors compared to incomplete models.
Ditching load sensors and directly embedding cable constraints into the quadrotor's control loop unlocks more precise and robust aerial manipulation.
This work proposes a novel control and estimation approach for aerial manipulation of a cable-suspended load using Unmanned Aerial Vehicles (UAVs). Common approaches in the state of the art have practical limitations, relying on direct load measurements and Lagrangian methods for dynamic modeling. The lack of a straightforward dynamic model of the system led us to propose adopting the Udwadia-Kalaba method to explicitly incorporate the cable's geometric constraints. This formulation allowed for the consistent derivation of the tension force and its direct integration into the NMPC prediction model. Additionally, we propose a sensorless load state estimation based on the same geometric constraints. Results from real-robot experiments demonstrated that the explicit inclusion of load dynamics in the optimization problem significantly reduces trajectory-tracking errors and yields better overall performance compared to strategies based on incomplete models.
