A Hybrid Modelling Approach for Aerial Manipulators. Kremer, P., Sanchez-Lopez, J. L., & Voos, H. June, 2022. arXiv:2206.08644 [cs]![A Hybrid Modelling Approach for Aerial Manipulators [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Aerial manipulators (AM) exhibit particularly challenging, non-linear dynamics; the UAV and the manipulator it is carrying form a tightly coupled dynamic system, mutually impacting each other. The mathematical model describing these dynamics forms the core of many solutions in non-linear control and deep reinforcement learning. Traditionally, the formulation of the dynamics involves Euler angle parametrization in the Lagrangian framework or quaternion parametrization in the Newton-Euler framework. The former has the disadvantage of giving birth to singularities and the latter being algorithmically complex. This work presents a hybrid solution, combining the benefits of both, namely a quaternion approach leveraging the Lagrangian framework, connecting the singularity-free parameterization with the algorithmic simplicity of the Lagrangian approach. We do so by offering detailed insights into the kinematic modeling process and the formulation of the dynamics of a general aerial manipulator. The obtained dynamics model is validated experimentally against a real-time physics engine. A practical application of the obtained dynamics model is shown in the context of a computed torque feedback controller (feedback linearization), where we analyze its real-time capability with increasingly complex models.
@misc{kremer_hybrid_2022,
title = {A {Hybrid} {Modelling} {Approach} for {Aerial} {Manipulators}},
url = {http://arxiv.org/abs/2206.08644},
doi = {10.1007/s10846-022-01640-1},
abstract = {Aerial manipulators (AM) exhibit particularly challenging, non-linear dynamics; the UAV and the manipulator it is carrying form a tightly coupled dynamic system, mutually impacting each other. The mathematical model describing these dynamics forms the core of many solutions in non-linear control and deep reinforcement learning. Traditionally, the formulation of the dynamics involves Euler angle parametrization in the Lagrangian framework or quaternion parametrization in the Newton-Euler framework. The former has the disadvantage of giving birth to singularities and the latter being algorithmically complex. This work presents a hybrid solution, combining the benefits of both, namely a quaternion approach leveraging the Lagrangian framework, connecting the singularity-free parameterization with the algorithmic simplicity of the Lagrangian approach. We do so by offering detailed insights into the kinematic modeling process and the formulation of the dynamics of a general aerial manipulator. The obtained dynamics model is validated experimentally against a real-time physics engine. A practical application of the obtained dynamics model is shown in the context of a computed torque feedback controller (feedback linearization), where we analyze its real-time capability with increasingly complex models.},
urldate = {2022-07-04},
author = {Kremer, Paul and Sanchez-Lopez, Jose Luis and Voos, Holger},
month = jun,
year = {2022},
note = {arXiv:2206.08644 [cs]},
keywords = {mentions sympy, multibody dynamics, robotics},
}
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