Yuhan Liu

I am a research assistant in Existential Robotics Laboratory (ERL) at University of California, San Diego (UCSD), advised by Prof. Nikolay Atanasov. Before that, I received my M.S. from UCSD in 2021 and B.Eng. from The Chinese University of Hong Kong, Shenzhen (CUHKSZ) in 2019.

I have been fortunate enough to work with Manmohan Chandraker, Henrik Christensen, and Xiaoguang Han on reinforcement learning, auto-calibration, and computer vision.

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My research interests lie in robotics and machine learning. I'd like to generalize policy learning algorithms to unseen environments and long-horizon/multi-stage tasks by leveraging expert demonstrations.

Learning Physics-Aware Rearrangement in Indoor Scenes
Meng Song, Yuhan Liu, Zhengqin Li, Manmohan Chandraker
video / paper

Two challenging tasks for testing agent's knowledge of friction and mass, as well as a novel energy-aware reward function to achieve the tasks.

Autonomous Vehicles for Micro-mobility
Henrik Christensen, David Paz, Hengyuan Zhang, Dominique Meyer, Hao Xiang, Yunhai Han, Yuhan Liu, Andrew Liang, Zheng Zhong, Shiqi Tang
Autonomous Intelligent Systems (AIS), 2021

A thorough documentation of the research effort of design, prototyping, and evaluation of a full stack autonomous vehicle for micro-mobility in UCSD. A valuable overview of a state-of-the-art autonomous driving study. A intriguing guidance for future research directions.

OpenRooms: An Open Framework for Photorealistic Indoor Scene Datasets
Zhengqin Li, Ting-Wei Yu, Shen Sang, Sarah Wang, Meng Song, Yuhan Liu, Yu-Ying Yeh, Rui Zhu, Nitesh Gundavarapu, Jia Shi, Sai Bi, Zexiang Xu, Hong-Xing Yu, Kalyan Sunkavalli, Miloš Hašan, Ravi Ramamoorthi, Manmohan Chandraker
CVPR, 2021 (Oral)
project page / arXiv

A photorealistic indoor scene datasets with high-quality ground truth SVBRDF and spatially-varying lighting, which can be easily applied to training embodied AI for learning physical properties like mass, friction, and lighting.

Auto-calibration Method Using Stop Signs for Urban Autonomous Driving Applications
Yuhan Liu*, Yunhai Han*, David Paz, Henrik Christensen
ICRA, 2021
project page / arXiv

An end-to-end pipeline for continuously updating intrinsic parameters of on-board cameras by recognition of traffic signs.

Modified from Jon Barron.