Papers
207
Total Citations
4,350
H-Index
32
About
Yaonan Wang is a prolific researcher whose work spans robotics, control systems, computer vision, and artificial intelligence. He has made foundational contributions to the fields of mobile robot control and multi-robot coordination, with his highly cited 2015 paper on simultaneous stabilization and tracking of nonholonomic mobile robots — garnering 160 citations — introducing an elegant Lyapunov-based framework that eliminated the need for switching strategies. His subsequent work on distributed leader-following formation control (156 citations) and vision-based formation strategies with field-of-view constraints further cemented his reputation as a leading voice in autonomous robotic systems. Wang has also advanced adaptive control for dual-arm robots and image-based visual servoing under uncertainty, demonstrating versatility across manipulation and perception challenges. His 2018 survey on semantic segmentation methods and datasets, the most-cited work in his portfolio with 278 citations, reflects his engagement with the broader deep learning community. More recently, his transformer-based imitative reinforcement learning approach for multi-robot path planning (103 citations) showcases his forward-looking integration of modern AI architectures into robotics. Across his career, Wang's research has consistently bridged rigorous theoretical control design with practical, real-world robotic applications.
Research Focus
Key Achievements
Top Papers
- 1Methods and datasets on semantic segmentation: A review278 citations · 2018
- 2
- 3
- 4
- 5
- 6
- 7Transformer-Based Imitative Reinforcement Learning for Multirobot Path Planning103 citations · 2023
- 8
- 9
- 10A Type-2 Fuzzy Switching Control System for Biped Robots88 citations · 2007