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About

Sheng Qi is a pioneering robotics researcher whose work bridges autonomous manipulation, human–robot collaboration, and healthcare robotics. Her primary research areas include mobile manipulator motion planning, physical human–robot interaction, and medical robotics—particularly the integration of Traditional Chinese Medicine (TCM) with robotic systems. Qi’s most impactful contribution is her development of capability map-based frameworks for autonomous and cooperative mobile manipulators. Her 2020 paper on a novel coordinated motion planner (55 citations) introduced a method that enables mobile manipulators to seamlessly coordinate base and arm movements, addressing the underconstrained redundancy challenge. She extended this work in 2022 (41 citations) by creating a capability map-based framework for cooperative transportation, allowing mobile manipulators to adapt in real-time to human motion during physical collaboration—a critical advance for safe human–robot teamwork. In healthcare, Qi has innovated with a real-time vision-based acupoint estimation system for TCM massage robots (11 citations) and a hybrid vision-force control method for soft tissue interaction (6 citations), tackling the nonlinear dynamics of biological tissues. Her work is notable for its practical impact on rehabilitation, surgery, and automation, earning recognition for advancing both fundamental robotics and applied medical technology.