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About

Ryan Dorosh is a robotics researcher advancing the frontier of soft growing manipulators—a class of robots that extend like vines to navigate complex, unstructured environments. His work bridges modeling, control, and human-robot interaction, with a focus on making soft robots practical for real-world applications. Dorosh’s most cited paper (2024, 10 citations) presents a continuous curvature-based model for soft growing robots, validated experimentally to improve precision in tasks like search and rescue. He also investigates the psychosocial impact of these robots, showing in a 2023 study (5 citations) that prior robot experience and proximity reduce perceived hazards and anxiety, supporting safer human-robot collaboration. In agricultural robotics, Dorosh has designed a lightweight soft electrical apple harvesting gripper (2024, 5 citations) and a low-cost, rapid-response manipulator for orchard operations (2023, 4 citations), addressing labor shortages with affordable, efficient solutions. His contributions are notable for integrating rigorous modeling with user-centered design, positioning soft growing robots as viable tools for both delicate manipulation and human interaction.