Papers
4
Total Citations
38
H-Index
3
About
Hongwen Li is a leading researcher in intelligent robotic control, with a primary focus on visual servoing, modular and reconfigurable robot systems, and human-robot interaction. His most influential work tackles the fundamental challenge of uncalibrated visual servoing for robot manipulators, where he developed a hybrid algorithm with feature constraints to maintain image features within the field of view under non-Gaussian noise—a paper that has garnered 22 citations. Li further advanced this field by introducing an optimal adaptive robust Kalman filter for online image Jacobian identification, overcoming the limitations of standard Kalman filters in handling uncertain noise covariances (11 citations). His contributions extend to modular and reconfigurable robots, where he proposed a non-zero-sum neural-optimal control method that balances control performance with energy efficiency, and a decentralized robust control approach for physical human-robot interaction that estimates human motion intention without relying on precise dynamic models. Through these innovations, Li has established himself as a key figure in developing robust, adaptive control strategies for next-generation robotic systems operating in unstructured environments.
Research Focus
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