Papers

3

Total Citations

47

H-Index

3

About

Xinfang Zhang is a leading researcher in robotics and computer vision, with a primary focus on visual servoing and autonomous navigation for wheeled mobile robots. Their work addresses critical challenges in enabling robots to operate without precise prior knowledge of their environment or hardware calibration. A key contribution is the development of a visual servoing approach that achieves simultaneous trajectory tracking and depth estimation without requiring desired velocity information, a breakthrough that simplifies control in unknown settings. Zhang further advanced the field by solving the visual trajectory tracking problem for wheeled mobile robots using uncalibrated camera extrinsic parameters, eliminating the need for the camera to be mounted at the robot’s center—a practical constraint in real-world deployments. In the domain of geometric vision, Zhang introduced an efficient 2-point algorithm for recovering relative pose and absolute scale from vehicle-mounted cameras under planar motion, significantly reducing computational demands. With over 47 citations across their most-cited works, Zhang’s research has directly impacted the development of more adaptable and cost-effective robotic systems, making them a notable figure in the intersection of control theory and computer vision.

Research Focus

Key Achievements

3
H-Index
3
Papers
47
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Visual Tracking and Depth Estimation of Mobile Robots Without Desired Velocity Information
21 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: State Key Laboratory of Industrial Control Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago