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About

Yan Zhi Tan’s research bridges the gap between perception, control, and automation in challenging industrial and underwater environments. His primary contributions lie in robotic welding, 3D point cloud processing, and underwater sensing. In his most-cited work (23 citations), Tan developed a framework for automated welding of tubular TKY joints—a critical task in marine and offshore construction—by fusing RGB-D sensor data with motion planning to adapt to real-world part poses. He further advanced geometric perception with novel edge and corner detection algorithms for unorganized point clouds, enabling precise feature extraction for robotic guidance. More recently, Tan has ventured into bio-inspired sensing, designing a self-spiking linear neuromorphic soft pressure sensor for underwater applications, mimicking the lateral line system of aquatic vertebrates. His work in sonar-based SLAM for structured underwater environments addresses the challenge of localization in turbid, featureless waters. Across his portfolio, Tan demonstrates a consistent focus on transforming raw sensor data into actionable robotic intelligence, with applications spanning heavy industry to autonomous underwater vehicles.