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Hybrid AI Architectures for Complex Aerial Manipulation |
PhD |
This PhD thesis will develop hybrid control architectures for aerial manipulation, combining model-based control and learning-based methods to enable reliable physical interaction with the environment. The project will investigate how predictive control, reinforcement learning, and multimodal sensing can be integrated to improve stability, precision, robustness, and adaptability during complex contact-rich manipulation tasks. The proposed methods will be validated in simulation and on real aerial robotic platforms. |
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Hardware Accelerators for Unmanned Aerial Vehicles MPC algorithms |
Master thesis |
The proposed MSc internship's objective is to design HW accelerators for UAV MPC algorithms, with the goal of improving accuracy, performance, power consumption, and silicon area. |
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Mechatronic Design of Aerial Robots for Aerial Manipulation and Collaborative Transportation |
Master thesis |
The goal of this Master Thesis is the design and validation of novel aerial platforms for Aerial Physical Interaction and collaborative transportation. |
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MPC-based control of a cable-suspended load using multiple UAVs for dynamic motions |
Master thesis |
This project envisions developing the next generation of multi-UAV systems to achieve fast, safe, and robust manipulation of a cable-suspended load in the real world. |
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Full-body Design and Control of an Aerial Manipulator |
Master thesis |
A new torque-controlled arm is to be designed and implemented for the tilt-hex hexacopter platform in order to obtain a thrust-torque (optimal) control for the robot. |
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