Baoquan Li
Papers
28
Total Citations
641
H-Index
11
About
Baoquan Li is a leading researcher in robotics and autonomous systems, with a particular focus on visual servoing for wheeled and nonholonomic mobile robots. His work addresses fundamental challenges in robot perception and control, especially the critical problem of operating effectively under unknown or uncalibrated camera parameters and unknown depth information — conditions that frequently arise in real-world deployments. Li's most influential contribution, his 2016 paper on visual servoing with uncalibrated camera-to-robot parameters (110 citations), introduced a monocular strategy that circumvents the need for precise sensor calibration, significantly lowering practical barriers to deployment. He further advanced the field through acceleration-level control frameworks combining backstepping and dynamic surface control (72 citations), simultaneous depth identification during visual regulation (67 citations), and unified tracking-and-regulation strategies (65 citations). His 2021 virtual-goal-guided RRT approach innovatively integrates motion planning with visual servoing to enforce field-of-view and velocity constraints simultaneously. Collectively accumulating over 550 citations, Li's body of work — capped by a comprehensive 2021 survey on visual servoing for mobile robots — has helped define the theoretical and practical landscape of vision-based robot control, making him an essential reference for researchers entering this dynamic field.
Research Focus
Key Achievements
Top Papers
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- 8Visual Servoing of Wheeled Mobile Robots Without Desired Images40 citations · 2018
- 9Hybrid Visual Servo Trajectory Tracking of Wheeled Mobile Robots26 citations · 2018
- 10A survey on visual servoing for wheeled mobile robots25 citations · 2021