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About

Inna Sharf is a prominent robotics researcher whose work spans contact dynamics modeling, robotic manipulation, motion planning, and bio-inspired locomotion. Based at McGill University, she has made foundational contributions to understanding how robots interact physically with their environments and navigate complex spaces. Her most influential work, a 2002 literature survey on contact dynamics modeling (719 citations), remains an essential reference for researchers tackling the mathematical complexities of object collisions and constrained motion. Building on this, her 2003 study on contact stiffness and damping estimation (188 citations) provided critical tools for simulating robotic assembly operations, particularly in space applications. Her sampling-based A* path-planning algorithm (161 citations) elegantly bridged classical search methods with modern probabilistic planning, advancing autonomous robot navigation. Sharf's research extends impressively across domains: from flexible-link manipulator dynamics and reactionless dual-arm satellite capture strategies to hybrid wheeled-legged robots, worm-inspired medical crawlers, and underactuated bipedal running. This breadth reflects a career dedicated to solving real-world robotics challenges — whether in orbit, on rough terrain, or inside biological vessels. With over 1,400 citations across her key works, Sharf stands as a significant and versatile force in modern robotics research.