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About

Tai Wen Chang is a robotics researcher whose work bridges autonomous navigation, human-robot interaction, and mobile manipulation. His key research areas include tracked robot autonomy, service robotics, and social robot expressiveness. Chang’s most impactful contribution is his work on autonomous stair climbing for tracked robots, where he developed a controller that uses fuzzy logic and stair features from perception systems to enable smooth climbing and descending—a critical capability for robots operating in multi-storey environments. His paper on this topic has garnered 11 citations, reflecting its practical significance. In human-robot interaction, Chang advanced robot expressiveness by studying screen-based feedback to compensate for mechanical limitations, earning 9 citations for a user study that enhanced game-playing scenarios. He also contributed to human tracking and following in dynamic environments using 2D laser scanners, with 10 citations for his robust detection method. Additional work includes a hierarchical topological planner for multi-storey navigation and system architecture for interactive patrolling humanoid robots. Chang’s research demonstrates a consistent focus on making robots more autonomous, perceptive, and socially capable in real-world settings.