Direct Force Feedback Control and Online Multi-Task Optimization for Aerial Manipulators
Gabriele Nava, Quentin Sablé, Marco Tognon, Daniele Pucci, Antonio Franchi
Abstract
In this letter 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 position/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.
BibTeX
@inproceedings{ral2020_directforcefeedb,
title = {Direct Force Feedback Control and Online Multi-Task Optimization for Aerial Manipulators},
author = {Gabriele Nava and Quentin Sablé and Marco Tognon and Daniele Pucci and Antonio Franchi},
booktitle = {RA-L 2020},
year = {2020}
}