ERI: Discrete Variable Stiffness Grippers for Safe and Sustainable Marine Harvesting

This Engineering Research Initiation (ERI) award will advance fundamental research in robotic technologies for safer and more sustainable marine harvesting. The United States imports a large proportion of the seafood it consumes, while domestic fisheries continue to face labor shortages, demanding working conditions, and increasing pressure to improve productivity and seafood quality. Although many harvesting operations have become mechanized, sorting of live seafood aboard fishing vessels remains largely manual, resulting in repetitive injuries, reduced processing efficiency, and prolonged exposure of seafood that lowers freshness and market value. This award supports fundamental research to enable robotic systems capable of handling a wide variety of live marine species safely and efficiently through a novel gripper design. The knowledge generated through this project is expected to improve automation technologies for the seafood industry, strengthen the competitiveness of domestic fisheries, enhance workplace safety, and promote sustainable use of marine resources through improved handling and more timely release of bycatch. This effort will integrate research into engineering education by improving robotics course materials, providing hands-on research opportunities for undergraduates through capstone projects and project work, organizing K-12 STEM summer camps, and strengthening collaborations with regional fisheries. Current robotic grippers often struggle to balance adaptability, robustness, precision, and safety when handling live seafood with a range of sizes, shapes, and mechanical properties. Existing approaches largely rely on continuously adjustable mechanisms that increase structural complexity, energy consumption, and control difficulty. This project will establish a fundamental framework for robotic grippers that rapidly transition among a limited number of stiffness states while maintaining simple mechanical designs and low energy requirements. The research will develop analytical and computational models that connect gripper structure, stiffness selection, and grasping performance; investigate adaptive control strategies capable of operating under disturbances produced by vessel motion, water flow, and animal movement; and develop vision-based perception methods that estimate grasp conditions without conventional contact force sensors. These concepts will be validated through laboratory experiments, robotic prototype testing, and representative marine harvesting scenarios. The resulting theories, design principles, and experimental knowledge are expected to establish a new foundation for compliant robotic manipulation and contribute broadly to intelligent automation in challenging marine environments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.