Student Projects

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Learning to Fly Soft Hovering Drones

Advances in aerial robotics and autonomy have led to remarkable achievements, primarily through multirotor drones with rigid frames. However, Nature offers a different paradigm: Animal wings are significantly more flexible than these rigid structures, yet they achieve highly efficient and agile flight. This project reimagines multirotor design by focusing on soft, deformable structures and leverages reinforcement learning (RL) to control their unique dynamics.

Keywords

Reinforcement Learning, RL, Aerial Robotics, Drones, Soft Robotics

Labels

Master Thesis

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Published since: 2025-03-07 , Earliest start: 2025-03-31 , Latest end: 2025-11-17

Organization Environmental Robotics Laboratory

Hosts Maquignaz Gabriel

Topics Information, Computing and Communication Sciences , Engineering and Technology

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