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This is the accompanying video of our RA-L paper titled "Adaptive Tank-based Control for Aerial Physical Interaction with Uncertain Dynamic Environments Using Energy-Task Estimation" https://ieeexplore.ieee.org/document/... Abstract: While aerial manipulation has witnessed noticeable growth as a field in the last decade, most works investigated forms of interaction with static and rigid environments only. Whenever dynamic environments were considered, the employed methods often relied on the knowledge of the model of the environment, which in most real applications cannot be obtained. In this work, we propose an adaptive controller for a fully actuated UAV performing stable and efficient physical interaction tasks with unmodeled and dynamic objects moving in unknown environments. We develop a passive time-varying impedance controller and wrench tracking controller, whose adaptable parameters allow us to minimize tracking error and instabilities during the execution of the interaction task. Robust stability is guaranteed by energy tanks, with the addition of a task-based formulation for adapting online the tank parameters in order to always provide the system with an adequate amount of energy. The control framework is validated both in simulations and experimentally by interacting with an unmodeled cart moving in passive time-varying environments, while subjected to unknown disturbances. Reference: F. Benzi, M. Brunner, M. Tognon, C. Secchi and R. Siegwart, "Adaptive Tank-based Control for Aerial Physical Interaction with Uncertain Dynamic Environments Using Energy-Task Estimation," in IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 9129-9136, Oct. 2022, doi: 10.1109/LRA.2022.3190074. PDF: https://www.research-collection.ethz....