Yu-Hsien Chang
Papers
1
Total Citations
26
H-Index
1
About
Yu-Hsien Chang is a robotics researcher whose work sits at the intersection of computer vision and intelligent manipulation, with a particular focus on enabling collaborative robots to perceive and interact with unstructured environments. His most cited contribution, "3D Vision for Object Grasp and Obstacle Avoidance of a Collaborative Robot" (2019, 26 citations), presents a pioneering design for robotic bin picking that integrates 3D vision algorithms to analyze cluttered scenes, classify objects, and estimate their poses for reliable grasping—all while dynamically avoiding obstacles. This work addresses a critical bottleneck in industrial automation: giving robots the perceptual intelligence to handle real-world disorder. Chang’s approach demonstrates how depth-sensing and geometric reasoning can transform a standard collaborative robot into an adaptive pick-and-place system, reducing the need for rigid, pre-programmed setups. His research has direct implications for manufacturing, logistics, and human-robot collaboration, where safe and flexible object handling is paramount. By bridging 3D computer vision with robotic control, Chang is helping to usher in a new generation of machines that see, understand, and act within our cluttered, three-dimensional world.
Research Focus
Key Achievements
Top Papers
- 13D Vision for Object Grasp and Obstacle Avoidance of a Collaborative Robot26 citations · 2019