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About

Kui Xiang is a prominent robotics and automation researcher whose work spans human-robot interaction, motion sensing, robot navigation, and exoskeleton control systems. Best known for his comprehensive 2018 review on multimodal human hand motion sensing (77 citations), Xiang has made foundational contributions to understanding how human hand skills can be captured and transferred to dexterous robotic systems. His research on multiple-sensor-based hand motion recognition further demonstrated practical frameworks for prosthetics and human-computer interaction. Xiang's work extends into intelligent robot navigation, with his improved self-adaptive particle swarm optimization approach for multi-robot path planning (59 citations) offering meaningful advances in cooperative robotics. His 2019 study on personalized exoskeleton control through adaptive fuzzy inference (37 citations) highlights his commitment to human-centered rehabilitation technologies. Additional contributions in indoor localization using extended Kalman filter-based sensor fusion, biomechanically inspired balance control, and precision spherical joint sensing reflect the remarkable breadth of his technical expertise. With over 260 cumulative citations and recent survey work on robotics perception and control (2024), Xiang continues shaping the conversation around intelligent robotic systems, making his scholarship invaluable to students and engineers navigating the rapidly evolving intersection of sensing, control, and human-robot collaboration.