Chunhui Gao
Papers
7
Total Citations
58
H-Index
4
About
Chunhui Gao is a robotics researcher whose work spans robotic manipulation, multi-sensor integration, and industrial robot calibration — areas that sit at the intersection of intelligent manufacturing and autonomous systems. Gao's early contributions focused on robust grasp planning, most notably developing a center-of-mass-based regrasp planner that leverages tactile-visual sensor fusion to detect slip and dynamically correct unstable grasp poses, a paper that has garnered 24 citations and represents a significant advance in dexterous robotic handling of unknown objects. Building on this foundation, Gao investigated contact-rich manipulation through proactive visual residual reinforcement learning on torque-controlled robots, addressing the longstanding challenge of designing adaptive controllers for complex manufacturing tasks. More recently, Gao's research has pivoted toward improving the absolute positional accuracy of industrial robots, contributing kinematics parameter calibration methods based on partial pose measurement, support vector regression-based spatial error prediction, and a continuous recursive least-squares calibration framework designed to maintain accuracy over time as robot performance degrades. Collectively accumulating over 55 citations, Gao's portfolio demonstrates a coherent trajectory from intelligent grasping toward precision manufacturing — making this body of work highly relevant for researchers and engineers working on next-generation smart factory systems.
Research Focus
Key Achievements
Top Papers
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