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About

William G. Wee is a researcher whose work sits at the intersection of artificial intelligence, robotics, and automated manufacturing systems. He is best known for his pioneering contributions to knowledge-based planning for robotic assembly, a field that gained significant momentum in the late 1980s as manufacturers sought to automate complex assembly tasks. His landmark 1988 paper, "A Knowledge-Based Planning System for Mechanical Assembly Using Robots," remains his most influential work with 44 citations, presenting a sophisticated AI-driven system capable of generating task-level assembly plans by drawing on structured knowledge bases encompassing workpiece geometry, assembly rules, and robot operations. This research laid important groundwork for intelligent automation in industrial robotics at a time when such integration was still largely experimental. Wee's earlier 1985 contributions introduced the foundational concepts that would be refined in his later work, demonstrating a sustained commitment to advancing task-level robot planning. His research portfolio also extends into computer vision and infrared imaging, with applied work on detecting and classifying cooling holes in aircraft engine blades — reflecting his broader interest in deploying intelligent systems for precision industrial inspection. Wee's body of work represents a meaningful bridge between classical AI planning and real-world robotic applications.