Jinghai Zhu
Papers
4
Total Citations
116
H-Index
3
About
Dr. Jinghai Zhu is a leading researcher in intelligent robotics, specializing in the critical challenge of force and position control for mobile manipulators. His work masterfully integrates advanced adaptive control theory with neural network architectures to solve real-world robotic problems. Dr. Zhu’s most influential contribution, with 70 citations, is his pioneering "Elman Fuzzy Adaptive Control for Obstacle Avoidance," which introduced a novel hybrid force/position control method that uses a virtual force field to maintain a safe distance between robots and obstacles, dynamically compensating for environmental uncertainties. He further advanced the field by applying Quantitative Feedback Theory to the persistent problem of end-point contact force control, a key paper that has garnered 32 citations. Dr. Zhu’s research is distinguished by its rigorous theoretical foundation, including the use of Hamilton-Jacobi-Isaacs principles for robust control, and its practical focus on enabling robots to interact safely and precisely with their environment. His work is essential reading for anyone interested in the intersection of adaptive control, neural networks, and autonomous robotic manipulation.
Research Focus
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Top Papers
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