Lawrence Yunliang Chen

I am a 4th year PhD student at UC Berkeley, advised by Professor Ken Goldberg. My research interest lies in the intersection of Robotics and Machine Learning. I am a member of the AUTOLAB, which is part of the Berkeley Artificial Intelligence Research (BAIR) Lab. I am supported by the NSF Graduate Research Fellowship. I did my undergraduate at UCLA with double majors in Applied Math and Statistics, where I was advised by Professor Jungseock Joo.

Email / CV / Google Scholar / LinkedIn / Twitter

Research

I'm broadly interested in robot learning, manipulation, and perception. Here are some of my research papers. Please feel free to reach out!

	Mirage: Cross-Embodiment Zero-Shot Policy Transfer with Cross-Painting Lawrence Yunliang Chen, Kush Hari, Karthik Dharmarajan, Chenfeng Xu, Quan Vuong, Ken Goldberg Preprint* PDF / Website Zero-shot transfer a visuomotor policy trained on one robot to unseen robot embodiments by cross-painting the images.
	DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset Alexander Khazatsky, Karl Pertsch, Suraj Nair, Ashwin Balakrishna, Sudeep Dasari, Siddharth Karamcheti, Soroush Nasiriany, Mohan Kumar Srirama, Lawrence Yunliang Chen, Kirsty Ellis, Peter David Fagan, Joey Hejna, Masha Itkina, Marion Lepert, Yecheng Jason Ma, Patrick Tree Miller, Jimmy Wu, Suneel Belkhale, Shivin Dass, Huy Ha, Arhan Jain, Abraham Lee, Youngwoon Lee, Marius Memmel, Sungjae Park, Ilija Radosavovic, Kaiyuan Wang, Albert Zhan, Kevin Black, Cheng Chi, Kyle Beltran Hatch, Shan Lin, Jingpei Lu, Jean Mercat, Abdul Rehman, Pannag R Sanketi, Archit Sharma, Cody Simpson, Quan Vuong, Homer Rich Walke, Blake Wulfe, Ted Xiao, Jonathan Heewon Yang, Arefeh Yavary, Tony Z. Zhao, Christopher Agia, Rohan Baijal, Mateo Guaman Castro, Daphne Chen, Qiuyu Chen, Trinity Chung, Jaimyn Drake, Ethan Paul Foster, Jensen Gao, David Antonio Herrera, Minho Heo, Kyle Hsu, Jiaheng Hu, Donovon Jackson, Charlotte Le, Yunshuang Li, Kevin Lin, Roy Lin, Zehan Ma, Abhiram Maddukuri, Suvir Mirchandani, Daniel Morton, Tony Nguyen, Abigail O'Neill, Rosario Scalise, Derick Seale, Victor Son, Stephen Tian, Emi Tran, Andrew E. Wang, Yilin Wu, Annie Xie, Jingyun Yang, Patrick Yin, Yunchu Zhang, Osbert Bastani, Glen Berseth, Jeannette Bohg, Ken Goldberg, Abhinav Gupta, Abhishek Gupta, Dinesh Jayaraman, Joseph J Lim, Jitendra Malik, Roberto Martín-Martín, Subramanian Ramamoorthy, Dorsa Sadigh, Shuran Song, Jiajun Wu, Michael C. Yip, Yuke Zhu, Thomas Kollar, Sergey Levine, Chelsea Finn Preprint PDF / Website / Hardware Code / Policy Learning Code A dataset that contains 76k demonstration trajectories or 350 hours of interaction data, collected across 564 scenes and 84 tasks by 50 data collectors over the course of 12 months.
	Open X-Embodiment: Robotic Learning Datasets and RT-X Models Open X-Embodiment Collaboration. Abhishek Padalkar, Acorn Pooley, Ajinkya Jain, Alex Bewley, Alex Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anikait Singh, Anthony Brohan, Antonin Raffin, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Brian Ichter, Cewu Lu, Charles Xu, Chelsea Finn, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Chuer Pan, Chuyuan Fu, Coline Devin, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Federico Ceola, Fei Xia, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Giulio Schiavi, Hao Su, Hao-Shu Fang, Haochen Shi, Heni Ben Amor, Henrik I Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jaehyung Kim, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey Bingham, Jiajun Wu, Jialin Wu, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jitendra Malik, Jonathan Tompson, Jonathan Yang, Joseph J. Lim, João Silvério, Junhyek Han, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Zhang, Keyvan Majd, Krishan Rana, Krishnan Srinivasan, Lawrence Yunliang Chen, Lerrel Pinto, Liam Tan, Lionel Ott, Lisa Lee, Masayoshi Tomizuka, Maximilian Du, Michael Ahn, Mingtong Zhang, Mingyu Ding, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J Joshi, Niko Suenderhauf, Norman Di Palo, Nur Muhammad Mahi Shafiullah, Oier Mees, Oliver Kroemer, Pannag R Sanketi, Paul Wohlhart, Peng Xu, Pierre Sermanet, Priya Sundaresan, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Sherry Moore, Shikhar Bahl, Shivin Dass, Shuran Song, Sichun Xu, Siddhant Haldar, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Sudeep Dasari, Suneel Belkhale, Takayuki Osa, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xuanlin Li, Yao Lu, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Ying Xu, Yixuan Wang, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yueh-hua Wu, Yujin Tang, Yuke Zhu, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zhuo Xu, Zichen Jeff Cui IEEE International Conference on Robotics and Automation (ICRA), 2024 PDF / Website / Blog Post / Code / Data We introduce the Open X-Embodiment Dataset, the largest open-source real robot dataset to date. We train two models on the robotics data mixture: RT-1-X and RT-2-X.
	Language Embedded Radiance Fields for Zero-Shot Task-Oriented Grasping Adam Rashid, Satvik Sharma, Chung Min Kim, Justin Kerr, Lawrence Yunliang Chen, Angjoo Kanazawa, Ken Goldberg Conference on Robot Learning (CoRL), 2023 (Oral Presentation, 6.6%) (Best Paper/Best Student Paper Finalist) PDF / Website / Code / Data Given a natural language query, uses LERF based on CLIP and DINO features to perform zero-shot semantic grasping of object parts.
	Semantic Mechanical Search with Large Vision and Language Models Satvik Sharma, Huang Huang, Kaushik Shivakumar, Lawrence Yunliang Chen, Ryan Hoque, Brian Ichter, Ken Goldberg Conference on Robot Learning (CoRL), 2023 PDF / Website Uses VLMs and LLMs to create semantic distributions that can be integrated into downstream mechanical search policies.
	Bagging by Learning to Singulate Layers Using Interactive Perception Lawrence Yunliang Chen, Baiyu Shi, Roy Lin, Daniel Seita, Ayah Ahmad, Richard Cheng, Thomas Kollar, David Held, Ken Goldberg IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023 (Best Industrial Robotics Research for Applications Finalist) PDF / Website An algorithm for grasping a single layer of plastic bags and fabrics using purely visual feedback, and a much-improved bagging algorithm.
	AutoBag: Learning to Open Plastic Bags and Insert Objects Lawrence Yunliang Chen, Baiyu Shi, Daniel Seita, Richard Cheng, Thomas Kollar, Ken Goldberg IEEE International Conference on Robotics and Automation (ICRA), 2023 PDF / Website A semantic representation of plastic bags and an algorithm for a bimanual robot to open a plastic bag from unstructured configurations, to insert object(s) into it, and then to lift the bag.
	Fleet-DAgger: Interactive Robot Fleet Learning with Scalable Human Supervision Ryan Hoque, Lawrence Yunliang Chen, Satvik Sharma, Karthik Dharmarajan, Brijen Thananjeyan, Pieter Abbeel, Ken Goldberg Conference on Robot Learning (CoRL), 2022 (Oral Presentation, 6.5%) PDF / Website / Code A formalism, several new algorithms, and a benchmark for interactive fleet learning: interactive learning with multiple robots and multiple humans.
	Efficiently Learning Single-Arm Fling Motions to Smooth Garments Lawrence Yunliang Chen, Huang Huang, Ellen Novoseller, Daniel Seita, Jeffrey Ichnowski, Michael Laskey, Richard Cheng, Thomas Kollar, Ken Goldberg The International Symposium on Robotics Research (ISRR), 2022 PDF / Website Given a new garment, quickly learn a fling action that can effectively smooth the garment with only one robot arm.
	Optimal Shelf Arrangement to Minimize Robot Retrieval Time Lawrence Yunliang Chen, Huang Huang, Michael Danielczuk, Jeffrey Ichnowski, Ken Goldberg IEEE International Conference on Automation Science and Engineering (CASE), 2022 (Best Student Paper Finalist) PDF / Website Optimize the arrangement of objects on a shelf to make them easier to retrieve and search.
	Real2Sim2Real: Self-Supervised Learning of Physical Single-Step Dynamic Actions for Planar Robot Casting Vincent Lim, Huang Huang, Lawrence Yunliang Chen, Jonathan Wang, Jeffrey Ichnowski, Daniel Seita, Michael Laskey, Ken Goldberg IEEE International Conference on Robotics and Automation (ICRA), 2022 PDF / Website / Video / Press Using Real2Sim2Real to learn to manipulate a free-end cable so that the endpoint can accurately reach desired target positions on a planar surface.
	A Multi-Chamber Smart Suction Cup for Adaptive Gripping and Haptic Exploration Tae Myung Huh, Kate Sanders, Michael Danielczuk, Monica Li, Yunliang Chen, Ken Goldberg, Hannah S. Stuart IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021 PDF / Video A new suction cup design that contains multiple chambers for gripping and haptic exploration.
	Understanding and Mitigating Annotation Bias in Facial Expression Recognition Yunliang Chen, Jungseock Joo IEEE/CVF International Conference on Computer Vision (ICCV), 2021 PDF (with appendix) / Code Analysis of annotation bias for many large public facial expression recognition datasets.

Class Projects

Anki Overdrive: Static Obstacle Detection and Avoidance
Lawrence Yunliang Chen, Massimiliano de Sa, Satvik Sharma, Vainavi Viswanath
Project advisor and sponsor: Jun Zeng
Website / Code

Berkeley EECS C106A/206A (Introduction to Robotics) Final Project

Honors & Awards

Grassi Fellowship, 2023-24
Berkeley IEOR Department's endowed PhD fellowship, one awardee per year

Katta G. Murty Prize for Best Paper in Optimization, 2023
For the paper "Optimal Shelf Arrangement and Rearrangement to Minimize Robot Retrieval Time," IEOR Department, UC Berkeley

NSF Graduate Research Fellowship, 2022-25
NSF Graduate Research Fellowship Program (GRFP)

Scholarship for the International Elite Summer School in Robotics and Entrepreneurship, 2022
Funded by the Danish Ministry of Higher Education and Science, Odense Municipality, the Innovation Centre Denmark, the Novo Nordisk Foundation, and private partners

Chiang Fellowship for Graduate Scholars in Manufacturing and Engineering, 2020-21
UC Berkeley IEOR Departmental Fellowship

Teaching

Graduate Student Instructor, IEOR 215: Analysis and Design of Databases, Spring 2022

Website template from Jon Barron