Papers
12
Total Citations
672
H-Index
9
About
Sing Bing Kang is a computer vision and robotics researcher whose career has centered on two interconnected themes: robot learning from human demonstration and panoramic vision systems. His most influential body of work pioneers the "Assembly Plan from Observation" (APO) paradigm, a groundbreaking framework enabling robots to observe, understand, and replicate human grasping tasks with minimal intervention. Beginning with foundational work in 1991 and extending through the 2000s, Kang systematically advanced this paradigm across multiple dimensions — from grasp recognition and temporal segmentation of task sequences to the direct mapping of human grasps onto robotic manipulators — accumulating hundreds of citations across the series. His 1997 paper on mapping human grasps to manipulator grasps (160 citations) stands as his most impactful individual contribution, while his 1993 work on grasp recognition from observation (120 citations) established critical early groundwork. Beyond robotics, Kang co-authored the widely referenced volume *Panoramic Vision: Sensors, Theory, and Applications* (2001, 151 citations), demonstrating breadth in computational imaging. Collectively, his research has profoundly shaped how robots can be intuitively programmed through human demonstration rather than explicit coding, influencing generations of researchers in robot learning and manipulation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Panoramic vision : sensors, theory, and applications151 citations · 2001
- 3
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- 5Robot instruction by human demonstration41 citations · 1995
- 6Grasp Recognition Using The Contact Web34 citations · 2005
- 7A robot system that observes and replicates grasping tasks30 citations · 2002
- 8A Framework for Recognizing Grasps17 citations · 1991
- 9Robot task programming by human demonstration10 citations · 1995
- 10A Scalable Video Rate Camera Interface7 citations · 1994