Dangguo Shao
Papers
1
Total Citations
2
H-Index
1
About
Dangguo Shao is a researcher whose work bridges robotics, computer vision, and control systems, with a particular focus on enhancing the precision and reliability of autonomous robot operations. His key research areas include visual servo control, image stabilization, and motion compensation algorithms for mobile robots. Shao’s major contribution lies in the design of a jitter compensation algorithm for robot vision, which addresses the critical challenge of image instability caused by uneven terrain—such as brick roads—that degrades the accuracy of vision-based robot control. By integrating optical flow techniques with Kalman filtering, he developed a method that uses affine transformation kinematics to extract six image motion parameters, effectively stabilizing video feeds and improving operational precision. While his most cited work, "Design of Jitter Compensation Algorithm for Robot Vision Based on Optical Flow and Kalman Filter" (2014), has garnered 2 citations, it represents a foundational step in practical visual stabilization for field robotics. Shao’s work is particularly notable for its direct application to real-world autonomous systems, offering a computationally efficient solution that enhances robot performance in unstructured environments. His research continues to inform advancements in robust visual perception for mobile robots.
Research Focus
Key Achievements
Top Papers
- 1