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Direct Force Feedback Control and Online Multi-task Optimization for Aerial Manipulators

Abstract : In this paper we present an optimization-based method for controlling aerial manipulators in physical contact with the environment. The multi-task control problem, which includes hybrid force-motion tasks, energetic tasks, and po-sition/postural tasks, is recast as a quadratic programming problem with equality and inequality constraints, which is solved online. Thanks to this method, the aerial platform can be exploited at its best to perform the multi-objective tasks, with tunable priorities, while hard constraints such as contact maintenance, friction cones, joint limits, maximum and minimum propeller speeds are all respected. An on-board force/torque sensor mounted at the end effector is used in the feedback loop in order to cope with model inaccuracies and reject external disturbances. Real experiments with a multi-rotor platform and a multi-DoF lightweight manipulator demonstrate the applicability and effectiveness of the proposed approach in the real world.
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Submitted on : Thursday, January 23, 2020 - 6:32:45 PM
Last modification on : Monday, April 4, 2022 - 3:24:38 PM
Long-term archiving on: : Friday, April 24, 2020 - 3:01:19 PM

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Gabriele Nava, Quentin Sablé, Marco Tognon, Daniele Pucci, Antonio Franchi. Direct Force Feedback Control and Online Multi-task Optimization for Aerial Manipulators. IEEE Robotics and Automation Letters, IEEE 2020, 5 (2), pp.331-338. ⟨10.1109/LRA.2019.2958473⟩. ⟨hal-02453407⟩

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