Modular Adaptive Aerial Manipulation under Unknown Dynamic Coupling Forces
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Abstract (arXiv)
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. Additionally, 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 sub-dynamics, the vehicle attitude sub-dynamics, and the manipulator sub-dynamics. 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.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Oct 2024.
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Citing papers per year: 2026: 3.
3 papers.
- 2026Strain-Parameterized Coupled Dynamics and Dual-Camera Visual Servoing for Aerial Continuum Manipulatorscited by 1
- 2026Reinforcement Learning with Inner-loop Dynamics Estimator for Aerial Manipulation under Uncertaintycited by 1
- 2026Fly-by-Code: Embodied Coding Agents for Aerial Manipulation with Active Visual and Physical Feedbackcited by 0
- 2026Fly-by-Code: Embodied Coding Agents for Aerial Manipulation with Active Visual and Physical Feedback8 Oct 2026
- 2026Reinforcement Learning with Inner-loop Dynamics Estimator for Aerial Manipulation under Uncertainty15 Jun 2026
- 2026Strain-Parameterized Coupled Dynamics and Dual-Camera Visual Servoing for Aerial Continuum Manipulators24 Mar 2026