Soft Rigid

Soft-rigid hybrid robots combine the compliance and safety of soft robots with the strength and payload capacity of rigid robots, aiming to overcome limitations of each individual approach. Current research focuses on developing accurate, computationally efficient models—often employing strain-based methods and model order reduction techniques like Proper Orthogonal Decomposition—and robust control algorithms, including Control Barrier Functions, to manage complex dynamics, especially self-contact. This field is significant for advancing robotic capabilities in unstructured environments, with applications ranging from safe human-robot interaction to challenging tasks like explosive ordnance disposal, where the unique properties of these hybrid systems offer substantial advantages.