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About

Chien-Wu Lan is a robotics researcher whose work focuses on bridging the gap between autonomous perception and physical action in humanoid and service robots. His primary research areas include computer vision, neural-network-based control systems, and autonomous navigation for robotic platforms. Lan’s most significant contributions lie in developing active embedded vision systems that enable humanoid robots to perform complex tasks like searching for, tracking, and kicking a ball to a dynamically estimated virtual target point—a challenging problem requiring real-time visual processing and motor coordination. His 2013 paper on this neural-network-based system has garnered 28 citations, demonstrating its influence in the field. Lan has also advanced practical, low-cost robotics, designing an autonomous patrol system using stereo vision and checking flags that eliminates the need for expensive pre-mapped paths, and developing a portable LoRa-based teleoperation controller for Industry 4.0 applications. By comparing visual navigation strategies and prioritizing affordability, Lan’s work makes sophisticated robotic behaviors more accessible, contributing to the democratization of autonomous systems for security, industrial, and educational use.