Ming-Yang Cheng
Papers
1
Total Citations
8
H-Index
1
About
Ming-Yang Cheng is a researcher whose work sits at the intersection of robotics, computer vision, and control systems, with a particular focus on visual servoing and autonomous robotic motion. His contributions to the field of image-based visual servoing (IBVS) have advanced how robotic systems perceive and respond to their environments in real time. Cheng's notable 2018 work on dynamic performance improvement in direct image-based visual servoing for contour following addresses a critical challenge in translating visual feedback into precise velocity commands for robotic systems — a problem with significant implications for industrial automation, quadrotor navigation, and unmanned aerial vehicles. By refining how image feature velocity commands are processed and converted within the visual control loop, his research enhances the reliability and responsiveness of vision-guided robots operating in dynamic environments. Though his citation count remains emerging, with work accumulating citations that reflect a growing recognition within specialist communities, Cheng's research speaks directly to the practical demands of modern robotics. His work provides a meaningful bridge between theoretical control frameworks and real-world deployment in complex, vision-dependent applications, making him a valuable contributor to the evolving landscape of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1