Ming-Yi Chien
Papers
1
Total Citations
32
H-Index
1
About
Ming-Yi Chien is a robotics researcher whose work centers on intelligent manipulation and dynamic object interaction. His most impactful contribution, the "Moving Object Prediction and Grasping System of Robot Manipulator" (2022, 32 citations), addresses a core challenge in industrial automation: enabling robot manipulators to reliably grasp objects in motion. Chien’s system integrates moving object recognition with predictive algorithms to coordinate a two-finger gripper on both conveyor belts and rotating platforms. This work is notable for its practical, real-time approach to tracking and interception, bridging computer vision and control theory. By demonstrating robust performance on two distinct motion types—linear and circular—Chien’s research offers a versatile framework for logistics, assembly, and pick-and-place tasks. His contributions are particularly relevant to students and engineers seeking to implement adaptive grasping in dynamic environments, showcasing how sensor fusion and prediction can elevate robotic dexterity. With this foundational paper, Chien has established himself as a promising voice in the field of robotic manipulation and intelligent automation.
Research Focus
Key Achievements
Top Papers
- 1Moving Object Prediction and Grasping System of Robot Manipulator32 citations · 2022