Dr. ZENG Chao
| Address: | Universität Hamburg Faculty of Mathematics, Informatics and Natural Science Department Informatics, Group TAMS Vogt-Kölln-Str. 30 D-22527 Hamburg |
| Position: | Research Associate |
| Room: | F-427 |
| Phone: | +49 (0) 40 42883-2417 |
| E-mail: | chao.zeng AT uni-hamburg.de; mjzengc AT gmail.com |
About Me
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I am currently a Research Associate at TAMS group, Universität Hamburg, under the supervision of Prof. Jianwei Zhang. I received the Ph.D. degree in robotics and control
from South China University of Technology (SCUT), China, in 2019. I am now participating in the scientific research project DEXMAN (DEXMAN: Improving robot’s DEXterous MANipulability by learning stiffness-based human motor skills and visuo-tactile exploration) which is an international collaborative project together founded by DFG (Germany) and NSFC (China). The main goal of this project is to develop learning and control approaches based on multimodal data to improve the ability of robot dexterous and compliant manipulation.
We have research assistant positions available, please feel free to contact me!
Research Interests
- Robot imitation learning
- Learning compliant manipulation and grasping
- Learning adaptive control
- Human-robot physical interaction and collaboration
Theses Supervision Topics
- Meta parameter optimization of robot force controller, see here.
- Learning compliant manipulation based on demonstration and exploration, see here.
Key Publications
- C. Zeng, S. Li, B. Fang, Z. Chen, J. Zhang. Generalization of Robot Force-Relevant Skills through Adapting Compliant Profiles, IEEE Robotics and Automation Letters, 7(2), April 2022.
- C. Zeng*, S. Li*, Y. Jiang, Q. Li,Z. Chen, C. Yang, and J. Zhang, Learning compliant grasping and manipulation by teleoperation with adaptive force control, IROS2021.
- C. Yang, C. Zeng, and J. Zhang. (2021). Robot Learning Human Skills and Intelligent Control Design. CRC Press.
- C. Zeng, C. Yang, H. Cheng, and S. Dai, Simultaneously Encoding Movement and EMG-based Stiffness for Robotic Skill Learning, IEEE Transactions on Industrial Informatics, 2020, 17(2), 1244-1252.
- C. Zeng, C. Yang, Q. Li and S. Dai, Research Progress on Human-Robot Skill Transfer, Acta Automatica Sinica, 2019, 45(10): 1813-1828.
- C. Yang, C. Zeng, C. Fang, W. He, and Z. Li, A DMPs-Based Framework for Robot Learning and Generalization of human-like Variable Impedance Skills, IEEE/ASME Transactions on Mechatronics, 2018, 23(3), 1193-1203.
- Yang, C., C. Zeng, Liang, P., Li, Z., Li, R., & Su, C. Y. (2017). Interface design of a physical humanrobot interaction system for human impedance adaptive skill transfer. IEEE Transactions on Automation Science and Engineering, 15(1), 329-340.
Featured Pictures
Academic Service
- Topic Editor of Frontiers in Robotics and AI, Research Topic on "Advanced Learning Control in Physical Interaction Tasks", see here.
- Reviewer for several journals including IEEE TRO; IEEE RA-L; IEEE/ASME TMECH; IEEE T-ASE; IEEE TII; IEEE TIE; and conferences including ICRA, IROS, ARM.
