Papers
133
Total Citations
3,515
H-Index
33
About
Liang Ding is a prominent robotics researcher whose work sits at the intersection of intelligent control systems, mobile robotics, and human-robot interaction. His research spans three deeply interconnected domains: adaptive control for wheeled mobile robots, terramechanics and terrain-robot interaction mechanics, and reinforcement learning-based optimization for robotic systems. Ding has made landmark contributions to wheeled mobile robot (WMR) control, pioneering adaptive neural network and reinforcement learning frameworks that handle real-world complexities such as full-state constraints, skidding, slipping, and communication delays. His 2017 paper on adaptive impedance control for human-robot cooperation (171 citations) and his work on model predictive control using neurodynamics optimization (143 citations) exemplify his ability to bridge theoretical rigor with practical robotic application. Equally significant is his contributions to planetary rover mobility, with his 2013 study on foot-terrain interaction mechanics (159 citations) and subsequent wheel-terrain interaction models for sandy terrains providing foundational tools for extraterrestrial robot design and simulation. Collectively, Ding's ten most-cited papers have accumulated over 1,200 citations, reflecting his sustained influence across the robotics community. His research is particularly valuable for engineers and scientists developing autonomous robots capable of navigating complex, uncertain, and unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10