Lei Tai

Lei Tai (邰磊)

Research Engineer
Autonomous Driving Solutions, Huawei

Email: ltai AT connect DOT ust DOT hk

About Me

I got my PhD degree (thesis) in 2019 from The Hong Kong University of Science and Technology(HKUST), supervised by Ming Liu in RAM Lab. I received the B.S.(2012) and the M.S.(2014) in Engineering from Harbin Institute of Technology(HIT). In the last year of the undergraduate, I joined the ABU Robocon as a team member of HIT Competitive Robot Team. Since then, I started my robotics work. In 2017, I was a visiting researcher in AIS, University of Freiburg, working with Wolfram Burgard and Joschka Boedecker. I was also with City University of Hong Kong from Sep 2015 to Aug 2017 which is another long story...

Google Scholar / Github / CV / LinkedIn

Research

My research interests mainly include deep reinforcement learning and learning from demonstrations on mobile robots. I have also worked in exploration of reinforcement learning, 3D perception for autonomous driving and human gaze in imitation learning. Representative works are highlighted.

	MLOD: Awareness of Extrinsic Perturbation in Multi-LiDAR 3D Object Detection for Autonomous Driving. IROS, 2020 Jianhao Jiao, Peng Yun, Lei Tai, Ming Liu pdf/ bibtex/ video/ code/ project page
	MonoPair: Monocular 3D Object Detection Using Pairwise Spatial Relationships. CVPR, 2020 Yongjian Chen, Lei Tai, Kai Sun, Mingyang Li pdf / bib / supplement / page / video
	High-speed Autonomous Drifting with Deep Reinforcement Learning. IEEE Robotics and Automation Letters (RA-L), 2020 ICRA, 2020 Peide Cai, Xiaodong Mei, Lei Tai, Yuxiang Sun, Ming Liu arxiv / bibtex / page / video / code
	Visual-based Autonomous Driving Deployment from a Stochastic and Uncertainty-aware Perspective. IROS, 2019 Lei Tai, Peng Yun, Yuying Chen, Congcong Liu, Haoyang Ye, Ming Liu pdf / bibtex / video / code
	Gaze Training by Modulated Dropout Improves Imitation Learning. IROS, 2019 Utilizing Eye Gaze to Enhance the Generalization of Imitation Network to Unseen Environments. ICML workshop, 2019 Yuying Chen, Congcong Liu, Lei Tai, Ming Liu, Bertram Shi arXiv / bibtex
	A Gaze Model Improves Autonomous Driving. ETRA, 2019 Congcong Liu, Yuying Chen, Lei Tai, Haoyang Ye, Ming Liu, Bertram Shi bibtex / page / video
	Focal Loss in 3D Object Detection. IEEE Robotics and Automation Letters (RA-L), 2019 ICRA, 2019 Peng Yun, Lei Tai, Yuan Wang, Chengju Liu, Ming Liu pdf / bibtex / page / code
	VR-Goggles for Robots: Real-to-sim Domain Adaptation for Visual Control. IEEE Robotics and Automation Letters (RA-L), 2019 Jingwei Zhang, Lei Tai, Peng Yun, Yufeng Xiong, Ming Liu, Joschka Boedecker, Wolfram Burgard (*indicates equal contribution) pdf / bibtex / supplement / page / video
	Curiosity-driven Exploration for Mapless Navigation with Deep Reinforcement Learning. ICRA workshop, 2018 Oleksii Zhelo, Jingwei Zhang, Lei Tai, Ming Liu, Wolfram Burgard pdf / bibtex / page / video
	A Survey of Deep Network Solutions for Learning Control in Robotics: From Reinforcement to Imitation. arXiv 1612.07139 Lei Tai, Jingwei Zhang, Ming Liu, Joschka Boedecker, Wolfram Burgard (*indicates equal contribution) arXiv / bibtex
	Socially Compliant Navigation through Raw Depth Inputs with Generative Adversarial Imitation Learning. ICRA, 2018 Lei Tai, Jingwei Zhang, Ming Liu, Wolfram Burgard pdf / bibtex / dataset / video
	Neural SLAM: Learning to Explore with External Memory. arXiv 1706.09520 Jingwei Zhang, Lei Tai, Joschka Boedecker, Wolfram Burgard, Ming Liu arXiv / bibtex / video
	Virtual-to-real Deep Reinforcement Learning: Continuous Control of Mobile Robots for Mapless Navigation. IROS, 2017 Lei Tai, Giuseppe Paolo, Ming Liu, pdf / bibtex / video
	Towards Cognitive Exploration through Deep Reinforcement Learning for Mobile Robots. arXiv 1610.01733 Lei Tai, Ming Liu arXiv / bibtex
	PCA-aided Fully Convolutional Networks for Semantic Segmentation of Multi-channel fMRI. International Conference on Advanced Robotics, 2017 (best student paper award) Lei Tai, Haoyang Ye, Qiong Ye, Ming Liu pdf / bibtex
	A Robot Exploration Strategy Based on Q-learning Network. IEEE International Conference on Real-time Computing and Robotics(RCAR), 2016 Mobile robots exploration through cnn-based reinforcement learning. Robotics and Biomimetics, 2016 Lei Tai, Ming Liu pdf / bibtex
	A Deep-network Solution Towards Model-less Obstacle Avoidance. IROS, 2016 Autonomous exploration of mobile robots through deep neural networks. International Journal of Advanced Robotic Systems(IJARS), 2017 Lei Tai, Shaohua Li, Ming Liu pdf / bibtex / dataset

Service

Journal Reviewer for IJRR, AURO, NNLS, IJARS and RA-L.

Conference Reviewer for ICRA 2017-23, IROS 2016-23 and CoRL 2019.

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