Papers
6
Total Citations
39
H-Index
4
About
Hong Zhan is a robotics researcher whose work sits at the intersection of optimal control theory, human-robot interaction, and intelligent manipulation. His research primarily focuses on adaptive dynamic programming (ADP) applied to robot control systems, with particular emphasis on solving the challenges of actuator saturation, environment interaction, and compliant robot behavior. Zhan's most significant contributions center on developing ADP-enhanced admittance and impedance control frameworks that enable robots to interact safely and optimally with unknown environments. His 2021 paper combining admittance adaptation with ADP has garnered 15 citations, establishing a foundational approach to handling actuator constraints while maintaining compliant, task-effective behavior. His earlier 2020 work laid the theoretical groundwork for this direction, demonstrating iterative linear quadratic regulator methods for robot-environment interaction. Beyond single-arm systems, Zhan has extended his expertise to bimanual robotics, addressing the nuanced problem of internal force regulation when two manipulators jointly manipulate an object. More recently, his work has expanded into fixed-time control strategies and vision-force integrated assembly for inclined-hole tasks, demonstrating a broadening research scope toward practical industrial applications. Collectively accumulating nearly 40 citations, Zhan's contributions represent meaningful advances in making robotic manipulation more adaptive, safe, and physically intelligent.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6Assembly strategy for inclined-holes based on vision and force2 citations · 2025