Chao-Ping Tung

Papers

Total Citations

102

H-Index

About

Chao-Ping Tung is a robotics researcher whose work has significantly advanced the field of autonomous robotic assembly and human-robot interaction. Specializing in robot programming, task planning, and sensory integration, Tung has dedicated his career to reducing the complexity of teaching robots to perform real-world assembly tasks. His most influential contribution, "Automatic Learning of Assembly Tasks Using a DataGlove System" (2002, 62 citations), introduced a groundbreaking approach in which robots learn new tasks by observing human operators wearing motion-capture gloves — a method that dramatically simplified robot programming by making it more intuitive and accessible. This work helped lay conceptual groundwork for modern programming-by-demonstration techniques widely explored in robotics today. Complementing this, his earlier work on integrated frameworks for sensing, planning, and execution — demonstrated on the PUMA 762 robotic platform — showcased how autonomous robotic systems could coordinate perception and action seamlessly, pushing boundaries in robotic autonomy. Published in 1996 with 30 citations, this research remains a meaningful reference in the field. Across his body of work, Tung has contributed practical, systems-level solutions to fundamental challenges in robotics, making him a noteworthy figure in the evolution of intelligent manufacturing and autonomous assembly research.