Wen-June Wang

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About

Wen-June Wang is a leading researcher in robotics and intelligent systems, whose work bridges human-robot interaction and autonomous navigation. His key research areas include humanoid robotics, computer vision, and dynamic obstacle avoidance, with a focus on enabling robots to perceive and respond to complex environments. Wang’s major contributions are exemplified by his pioneering work on motion imitation, where he developed a three-stage process for humanoid robots to replicate human movements—encompassing data acquisition, modification, and ankle angle adjustment—as detailed in his highly cited 2011 paper on image recognition and force measurement. This study, with 43 citations, has significantly advanced the field of interactive robotics. Additionally, his 2014 paper on dynamic obstacle avoidance path planning introduced an innovative image-based parallel lines distance measurement system (IBPLDMS) for real-time obstacle detection and avoidance, showcasing his ability to integrate image processing with practical navigation solutions. Wang’s research has profound implications for developing safer, more adaptive robots, and his work continues to inspire students and researchers in robotics and artificial intelligence.