Modular Adaptive Aerial Manipulation Under Unknown Dynamic Coupling Forces

Journal Article (2025)
Author(s)

Rishabh Dev Yadav (The University of Manchester)

Swati Dantu (Czech Technical University)

Wei Pan (The University of Manchester)

S. Sun (TU Delft - Learning & Autonomous Control)

Spandan Roy (International Institute of Information Technology)

S Baldi (Southeast University)

Research Group
Learning & Autonomous Control
DOI related publication
https://doi.org/10.1109/TMECH.2024.3457806
More Info
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Publication Year
2025
Language
English
Research Group
Learning & Autonomous Control
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/publishing/publisher-deals Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
4
Volume number
30
Pages (from-to)
2688-2698
Reuse Rights

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Abstract

Successful aerial manipulation largely depends on how effectively a controller can tackle the coupling dynamic forces between the aerial vehicle and the manipulator. However, this control problem has remained largely unsolved as the existing control approaches either require precise knowledge of the aerial vehicle/manipulator inertial couplings, or neglect the state-dependent uncertainties especially arising during the interaction phase. This work proposes an adaptive control solution to overcome this long standing control challenge without any a priori knowledge of the coupling dynamic terms. In addition, in contrast to the existing adaptive control solutions, the proposed control framework is modular, that is, it allows independent tuning of the adaptive gains for the vehicle position subdynamics, the vehicle attitude subdynamics, and the manipulator subdynamics. Stability of the closed loop under the proposed scheme is derived analytically, and real-time experiments validate the effectiveness of the proposed scheme over the state-of-the-art approaches.

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