Lei TAI 邰磊

Ph.D. candidate

Robotics Institute, Department of Electronic and Computer Engineering

The Hong Kong University of Science and Technology

Email: ltai AT ust DOT hk


About Me

I am a fifth-year Ph.D. candidate in RAM Lab, The Hong Kong University of Science and Technology (HKUST), supervised by Prof. Ming Liu. 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. From March 2017 to Jan 2018, I was a visiting researcher in AIS lab, University of Freiburg, working with Prof. Joschka Boedecker and Prof. Wolfram Burgard. My research interests include deep reinforcement learning and learning from demonstrations on mobile robots.

[google scholar] [github] [CV]


Research Publications

Sensorimotor learning

  • End-to-end Driving Deploying through Uncertainty-Aware Imitation Learning and Stochastic Visual Domain Adaptation.
    Lei Tai, Peng Yun, Yuying Chen, Congcong Liu, Haoyang Ye, Ming Liu
    arXiv 1903.00821
    arXiv bib video

  • A Gaze Model Improves Autonomous Driving.
    Congcong Liu*, Yuying Chen*, Lei Tai, Haoyang Ye, Ming Liu, Bertram Shi
    ACM Symposium on Eye Tracking Research & Applications (ETRA), Denver, USA, 2019
    page video

  • VR-Goggles for Robots: Real-to-sim Domain Adaptation for Visual Control.
    Jingwei Zhang*, Lei Tai*, Peng Yun, Yufeng Xiong, Ming Liu, Joschka Boedecker, Wolfram Burgard
    (* indicates equal contribution)
    IEEE Robotics and Automation Letters (RA-L), 2019.
    link pdf bib supplement page video

  • Curiosity-driven Exploration for Mapless Navigation with Deep Reinforcement Learning.
    Oleksii Zhelo, Jingwei Zhang, Lei Tai, Ming Liu, Wolfram Burgard
    ICRA Workshop on Machine Learning in Planning and Control of Robot Motion, Brisbane, Australia, 2018.
    pdf bib page video

  • Socially Compliant Navigation through Raw Depth Inputs with Generative Adversarial Imitation Learning.
    Lei Tai, Jingwei Zhang, Ming Liu, Wolfram Burgard
    International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 2018.
    link pdf bib dataset video

  • Neural SLAM: Learning to Explore with External Memory.
    Jingwei Zhang, Lei Tai, Joschka Boedecker, Wolfram Burgard, Ming Liu
    arxiv 1706.09520
    arXiv bib video

  • Virtual-to-real Deep Reinforcement Learning: Continuous Control of Mobile Robots for Mapless Navigation.
    Lei Tai, Giuseppe Paolo, Ming Liu
    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017.
    link pdf bib video
  • A Survey of Deep Network Solutions for Learning Control in Robotics: From Reinforcement to Imitation.
    Lei Tai*, Jingwei Zhang*, Ming Liu, Joschka Boedecker, Wolfram Burgard
    (* indicates equal contribution)
    arxiv 1612.07139
    arXiv bib

  • Towards Cognitive Exploration through Deep Reinforcement Learning for Mobile Robots.
    Lei Tai, Ming Liu
    arxiv 1610.01733
    arXiv bib

  • A Deep-network Solution Towards Model-less Obstacle Avoidance.
    Lei Tai, Shaohua Li, Ming Liu
    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon,Korea, 2016.
    link pdf bib dataset

  • A Robot Exploration Strategy Based on Q-learning Network.
    Lei Tai, Ming Liu
    IEEE International Conference on Real-time Computing and Robotics (RCAR), Siem Reap,Cambodia 2016.
    link pdf bib

Multi-dimension Perception

  • Focal Loss in 3D Object Detection.
    Peng Yun, Lei Tai, Yuan Wang, Chengju Liu, Ming Liu
    IEEE Robotics and Automation Letters (RA-L), 2019.
    International Conference on Robotics and Automation (ICRA), Montreal, Canada, 2019.
    link pdf bib page code

  • PCA-aided Fully Convolutional Networks for Semantic Segmentation of Multi-channel fMRI.
    Lei Tai, Haoyang Ye, Qiong Ye, Ming Liu
    International Conference on Advanced Robotics (ICAR), Hong Kong, China, 2017.
    Best Student Paper Award.
    link pdf bib

All the research videos are also available at [bilibili].


Academic Service

  • Program Committee Member: ICVS 2017, RCAR 2016
  • Journal Reviewer: AURO, IEEE Trans-NNLS, IJARS, IEEE RA-L
  • Conference Reviewer: ICRA 2017-19, IROS 2016-19, NeurIPS 2019 Workshop

Misc