Welcome to AutoMan Research Lab @ NTU
AutoMan members, Oct 2023
The Automated Driving and Human-Machine System (AutoMan) Lab @ NTU has a wide range of research activities covering design, control and optimization of human-centric robotics, human-machine systems, and cyber-physical systems, with particular applications to advanced road vehicles.
Our AutoMan group is exploring
Scientific automation mechanisms to better understand humans.
Smarter autonomous robotics to guide and assist humans.
Safer automated vehicles to better serve humans.
Smoother automation to interact with humans.
Sustainable automobiles for humans.
These are what AutoMan stands for!
Dr. Chen Lv (吕辰)
Associate Professor
Director, AutoMan Research Lab
School of Mechanical and Aerospace Engineering Cluster Director in Future Mobility Solutions, ERI@N
Thrust Lead in Smart Mobility and Delivery, Continental-NTU Corp Lab
Program Lead in Next Generation AMR, Schaeffler-NTU Joint Lab
E: lyuchen@ntu.edu.sg
Recent AutoMan News
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Dr. Lianxin Zhang joined as a research fellow in Feb 2024. Welcome onboard!
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Dr. Andrea Piazzoni joined as a research fellow in Feb 2024. Welcome onboard!
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Dr. Lin Li joined as a research fellow in Jan 2024. Welcome onboard!
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Our work on brain-like AI for safe driving was featured as a news story in IEEE Spectrum. Cheers!
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Ji Yuan re-joined as a postdoc research fellow in December 2023. Welcome aboard!
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Songyan joined as a research associate (PhD 2024 Jan intake) in November. Welcome aboard!
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Dr. Shuo Cheng joined as a research fellow in November. Welcome aboard!
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Haozhuang joined as a PhD student. Welcome aboard!
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Zhiyu successfully defended his PhD thesis! Congrats Dr. Huang!
Research Highlights
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Binbin's work on multi-robot coordination was accepted to Automatica.
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Yang Lie's work on driver drowsiness detection was accepted to TITS.
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Xiangkun's work on brain-inspired RL for safe AV was accepted to IEEE TPAMI.
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Jingda's work on human-guided RL with sim-to-real transfer for autonomous navigation was accepted to IEEE TPAMI.
Useful Resources
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CFP-SS: Learning-powered prediction and decision-making for AVs, (code: kaf7g), ITSC 2023
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CFP-SS: Trustworthy Learning-Enabled CPS (code: b9kq7), CDC 2023.
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CFP-SS: Advances in Decision, Control, and Testing for Autonomous Driving (code: 7dh27), CDC 2023.
