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About

Bokai Xuan is a robotics researcher whose work bridges medical robotics and assistive technologies for elderly care. His primary research areas include fracture reduction robotics, human-robot interaction for bathing assistance, and computer vision for robot pose estimation. Xuan's most significant contribution lies in developing precision control systems for medical robots, particularly his 2022 study on pose error modeling and compensation for fracture reduction robots, which addresses critical accuracy challenges in orthopedic surgery by analyzing and correcting trajectory deviations caused by mechanism errors. This work has garnered 10 citations, establishing a foundation for safer surgical robotics. In assistive robotics, Xuan has pioneered learning-based control strategies for robot-assisted bathing, including an impedance sliding mode technique for non-repetitive tasks (2024, 7 citations) and deep learning-based semantic segmentation for human feature recognition in bath scrubbing robots (2024, 2 citations). His innovative icosahedron marker design for 6-DOF pose estimation (2021) offers improved stability and accuracy over conventional ArUco markers. Xuan's research demonstrates a consistent focus on enhancing robot precision and adaptability in real-world applications, from operating rooms to elderly care facilities, making him a notable contributor to both medical and assistive robotics.