Changjian Ying
Papers
2
Total Citations
14
H-Index
2
About
Changjian Ying is a robotics researcher specializing in the manipulation of deformable linear objects (DLOs) and precision automation for industrial assembly. His work addresses fundamental challenges in enabling robots to handle flexible, non-rigid materials—such as cables, ropes, and hoses—which are notoriously difficult to control due to their constantly changing shapes. Ying’s major contributions include developing novel pose estimation techniques for small, floating connectors attached to cable tips, a critical step toward automating the grasping and insertion of these components in circuit board assembly. His most cited paper (2022, 10 citations) tackles this exact problem, laying groundwork for more reliable electronics manufacturing. More recently, Ying has advanced the field with obstacle avoidance shape control for DLOs, integrating online parameter adaptation through differentiable simulation (2024, 4 citations). This work enables robots to dynamically adjust their manipulation strategies in real-time, improving performance in complex environments. His research bridges the gap between theoretical robotics and practical applications, with potential impacts spanning product assembly, surgical suturing, and beyond.
Research Focus
Key Achievements
Top Papers
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