Journal Articles IEEE Robotics and Automation Letters Year : 2020

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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Dates and versions

hal-02453407 , version 1 (23-01-2020)

Identifiers

Cite

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, 2020, 5 (2), pp.331-338. ⟨10.1109/LRA.2019.2958473⟩. ⟨hal-02453407⟩
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