Jump-and-flight locomotion for a hybrid aerial loco-manipulator using MPC

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master_Li_Yunju_2025.pdf (5.63 MB)

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School of Electrical Engineering | Master's thesis
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Date

2025-07-31

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Major/Subject

Autonomous Systems

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Degree programme

Master's Programme in ICT Innovation

Language

en

Pages

72

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Abstract

This thesis investigates the trajectory generation and control of agile locomotion for aerial manipulators by using optimal control for trajectory optimization and model predictive control (MPC) for real-time execution. The study formulates robot tasks as optimal control problems constrained by full-body dynamics that explore agile and dynamically feasible trajectories. These trajectories are performed through an MPC controller that solves the problem iteratively and applies the resulting commands in a closed-loop manner. To ensure real-time feasibility, the work employs a solver based on differential dynamic programming, with specific techniques to handle actuator bounds. The proposed approach is validated through simulations and experiments on an aerial manipulator with a hexarotor platform. The results demonstrate that combining trajectory optimization with MPC enables agile locomotion that would be difficult to achieve using traditional methods.

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Supervisor

Baumann, Dominik

Thesis advisor

Sola, Joan

Keywords

robotics, optimal control, model predictive control, agile locomotion, robotic aerial loco-manipulator, dynamics modeling

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https://urn.fi/URN:NBN:fi:aalto-202508196410

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[dipl] Sähkötekniikan korkeakoulu / ELEC