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About

Claudio Mucignat is a researcher at the forefront of soft bio-inspired robotics, with a primary focus on underwater locomotion and morphing structures. His work bridges biology and engineering, using soft robotic models to explore undulatory swimming performance in fish and ancient marine reptiles. A key contribution is the development of a biorobotic fish that integrates soft sensors and particle image velocimetry to measure body kinematics and propulsive efficiency—a breakthrough that circumvents the difficulty of studying live fish muscle activation. This work, cited 11 times, has provided unprecedented insight into aquatic locomotion. Mucignat has also advanced soft robotic morphing wings for unmanned underwater vehicles, enhancing adaptability and collision resilience through closed-cycle hydraulic actuation. His research extends to paleontology, where asymmetric fin shapes in soft robophysical models of ancient marine reptiles reveal how evolutionary changes in morphology affected swimming dynamics. Additionally, he has pioneered repetitive learning control for body caudal undulation using soft sensory feedback, enabling robots to discriminate between deformation modes. With a growing citation record and publications in high-impact venues, Mucignat is shaping the future of autonomous underwater exploration and bio-inspired design.