Dailin Zhang
Papers
7
Total Citations
121
H-Index
4
About
Dailin Zhang is a leading researcher in intelligent robotics and human-robot collaboration, with a focus on advanced sensing and control systems. His work centers on iterative learning control (ILC) for nonlinear trajectory tracking, where he developed neural-network-based methods that enable robots to learn and improve performance across multiple tasks—a contribution cited over 50 times. Zhang is also renowned for his innovations in force sensing technology, including the design of six-dimensional traction force sensors and tandem force sensors that simultaneously detect human-applied traction and contact forces. These sensors are critical for active compliance control and safe human-robot interaction in complex manufacturing scenarios. His integrated compensation methods address force disturbance issues, ensuring accurate force feedback in real-world applications. With over 120 total citations, Zhang’s research has directly advanced robot teaching, learning from demonstration, and precision manufacturing. Notable achievements include his work on monocular-vision-based pose measurement for shield machines and 3D reconstruction for large workpieces, demonstrating his versatility in solving practical industrial challenges. His contributions are shaping the future of collaborative robotics and intelligent automation.
Research Focus
Key Achievements
Top Papers
- 1Neural-Network-Based Iterative Learning Control for Multiple Tasks54 citations · 2020
- 2A six-dimensional traction force sensor used for human-robot collaboration38 citations · 2018
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- 4Development and Application of a Tandem Force Sensor7 citations · 2020
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