Papers
41
Total Citations
1,106
H-Index
19
About
Yanbiao Zou is a prominent robotics and automation researcher whose work centers on intelligent welding systems, computer vision, robot motion planning, and human-robot collaboration. He has made pioneering contributions to laser vision-based seam tracking, developing sophisticated systems that combine image processing, deep learning, and real-time control to guide welding robots with exceptional precision. His 2018 trilogy of seam tracking papers — collectively amassing nearly 285 citations — established foundational frameworks that have become reference points in automated welding research. Zou further advanced the field by integrating deep reinforcement learning into both seam tracking and laser vision calibration, producing end-to-end approaches that reduce human error and improve system accuracy. His 2021 work combining convolution filters with deep reinforcement learning (80 citations) exemplifies his signature approach of blending classical signal processing with modern AI. Beyond welding, Zou has made notable contributions to time-optimal robot trajectory planning and force-controlled grinding, as well as electromyography-driven human-robot collaboration systems. With over 675 citations across his top publications, his research has meaningfully shaped the intersection of intelligent robotics, machine vision, and manufacturing automation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Real-time seam tracking control system based on line laser visions86 citations · 2018
- 3A seam tracking system based on a laser vision sensor81 citations · 2018
- 4
- 5Time-optimal and Smooth Trajectory Planning for Robot Manipulators71 citations · 2020
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- 9Research on a real-time pose estimation method for a seam tracking system46 citations · 2019
- 10