Papers
7
Total Citations
181
H-Index
7
About
Hongli Cao is a robotics and control systems researcher whose work centers on advancing the frontiers of human-robot interaction, robotic force control, and teleoperation. His most significant contributions lie in the development of adaptive impedance and admittance control frameworks that address longstanding challenges in robotic contact operations — specifically, the dual problems of transient force overshoots and steady-state force tracking errors in uncertain and dynamic environments. Cao's most influential work, "Dynamic Adaptive Hybrid Impedance Control for Dynamic Contact Force Tracking in Uncertain Environments" (2019), has garnered 81 citations and introduced a novel hybrid approach that overcomes the limitations of traditional compliance control. This was complemented by subsequent work on smooth adaptive hybrid impedance control (47 citations) and, more recently, fuzzy fractional-order adaptive impedance controllers, demonstrating a consistent drive toward increasingly sophisticated and robust solutions. His research also extends to human-robot teleoperation, where he has explored EMG-based gesture control and vision-guided grasping systems, broadening the practical applicability of his work. With a publication record spanning 2019 to 2022 and a growing citation profile, Cao has established himself as a meaningful contributor to intelligent robotic manipulation and safe human-robot collaboration.
Research Focus
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