Papers
158
Total Citations
3,548
H-Index
33
About
Haibo Gao is a prominent robotics researcher whose work spans the mechanics of robot-terrain interaction, intelligent control systems, and autonomous mobile robotics. His research has made foundational contributions to understanding how legged and wheeled robots navigate complex, deformable terrains — a challenge critical to planetary exploration and field robotics. His 2013 study on foot-terrain interaction mechanics for legged robots (159 citations) introduced physics-grounded contact models that move beyond simplistic black-box approaches, while his subsequent work on planetary rover wheel-terrain interaction (99 citations) advanced terramechanics modeling for extraterrestrial environments. Equally influential is Gao's pioneering work in intelligent control, where he has developed adaptive neural network and reinforcement learning frameworks for wheeled mobile robots navigating real-world uncertainties including slippage, state constraints, and time delays. His 2017 paper introducing the first adaptive neural network control algorithm for fully state-constrained wheeled mobile systems (144 citations) exemplifies this line of contribution. Across teleoperation, hexapod locomotion, and adaptive dynamic programming, Gao's cumulative citation record of nearly 1,000 reflects the breadth and depth of his influence, making him an essential reference for researchers designing robust, intelligent robotic systems for unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10Adaptive motion control of wheeled mobile robot with unknown slippage69 citations · 2014