Jiabin Cao
Papers
5
Total Citations
45
H-Index
5
About
Jiabin Cao is a leading researcher in industrial robotics, specializing in high-precision motion control, trajectory planning, and condition monitoring for robotic manipulators. His work addresses critical challenges in robot accuracy and efficiency, particularly through innovations in harmonic reducer performance and compensation. In his 2024 paper on calibration for high-accuracy harmonic reducers (13 citations), Cao developed a method that significantly improves end-effector positioning, a foundational contribution to precision manufacturing. He further advanced trajectory optimization with a segmented adaptive feedrate scheduling algorithm (10 citations) that enforces joint jerk constraints, enabling smoother and faster 6R robot motion. Cao’s earlier predictive model for harmonic reducer degradation (9 citations) uses multivariate state estimation and dimensionality reduction to preempt failures, enhancing operational reliability. His research on planar NURBS interpolation (7 citations) and redundant degree-of-freedom optimization for robotic milling (6 citations) directly addresses vibration and surface quality in machining. With a growing citation impact and a focus on bridging simulation to real-world industrial application, Cao is shaping the next generation of intelligent, high-accuracy robotic systems.
Research Focus
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Top Papers
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