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Article Dans Une Revue Autonomous Robots Année : 2023

Multi-directional Interaction Force Control with an Aerial Manipulator Under External Disturbances

Résumé

Abstract To improve accuracy and robustness of interactive aerial robots, the knowledge of the forces acting on the platform is of uttermost importance. The robot should distinguish interaction forces from external disturbances in order to be compliant with the firsts and reject the seconds. This represents a challenge since disturbances might be of different nature (physical contact, aerodynamic, modeling errors) and be applied to different points of the robot. This work presents a new $$\hbox {extended Kalman filter (EKF)}$$ extended Kalman filter (EKF) based estimator for both external disturbance and interaction forces. The estimator fuses information coming from the system’s dynamic model and it’s state with wrench measurements coming from a Force-Torque sensor. This allows for robust interaction control at the tool’s tip even in presence of external disturbance wrenches acting on the platform. We employ the filter estimates in a novel hybrid force/motion controller to perform force tracking not only along the tool direction, but from any platform’s orientation, without losing the stability of the pose controller. The proposed framework is extensively tested on an omnidirectional aerial manipulator (AM) performing push and slide operations and transitioning between different interaction surfaces, while subject to external disturbances. The experiments are done equipping the AM with two different tools: a rigid interaction stick and an actuated delta manipulator, showing the generality of the approach. Moreover, the estimation results are compared to a state-of-the-art momentum-based estimator, clearly showing the superiority of the EKF approach.
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hal-04197193 , version 1 (05-09-2023)

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Grzegorz Malczyk, Maximilian Brunner, Eugenio Cuniato, Marco Tognon, Roland Siegwart. Multi-directional Interaction Force Control with an Aerial Manipulator Under External Disturbances. Autonomous Robots, 2023, pp.1-21. ⟨10.1007/s10514-023-10128-2⟩. ⟨hal-04197193⟩
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