News

I am on the job market! Please reach out if you think I would be a good fit for your department or your team.
We are organizing Workshop on Towards Reliable and Deployable Learning-Based Robotic Systems at CoRL 2023.

Research

My research vision centers on enabling robust long-term autonomy for complex real-world systems such as industrial or household robots; drawing on tools and concepts from machine learning, controls, and robotics. Towards that end, my research agenda is focused on developing algorithms and establishing foundational principles for the design of high-performance, learning-based robotic systems, with the ultimate goal of deploying them successfully in complex, real-world environments.

Selected Publications [ Full List ]

	Octo: An Open-Source Generalist Robot Policy Octo Model Team ArXiv Preprint Paper \| Code
	SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning Jianlan Luo, Zheyuan Hu, Charles Xu, Siri Gadipudi, Archit Sharma, Rehaan Ahmad, Stefan Schaal, Chelsea Finn, Abhishek Gupta, Sergey Levine International Conference on Robotics and Automation (ICRA) 2024 arXiv \| Video \| Code \| Media Coverage
	FMB: A Functional Manipulation Benchmark for Generalizable Robotic Learning Jianlan Luo, Charles Xu, Fangchen Liu, Liam Tan, Zipeng Lin, Jeffrey Wu, Pieter Abbeel, Sergey Levine Under review at International Journal of Robotics Research (IJRR) arXiv \| Video \| Data
	RLIF: Interactive Imitation Learning as Reinforcement Learning Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine International Conference on Learning Representations (ICLR) 2024 arXiv \| Video \| Code \| Media Coverage 1, 2, 3, 4
	Open X-Embodiment: Robotic Learning Datasets and RT-X Models Open X-Embodiment Collaboration International Conference on Robotics and Automation (ICRA) 2024 arXiv \| Blog Post \| Dataset
	Multi-Stage Cable Routing through Hierarchical Imitation Learning Jianlan Luo, Charles Xu, Xinyang Geng, Gilbert Feng, Kuan Fang, Liam Tan, Stefan Schaal, Sergey Levine IEEE Transactions on Robotics (T-RO) 2024 arXiv \| T-RO version \| Video \| Code \| Dataset \| Data in tfds
	Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning Jianlan Luo, Perry Dong, Jeffrey Wu, Aviral Kumar, Xinyang Geng, Sergey Levine Conference on Robot Learning (CoRL) 2023 arXiv \| Code
	REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation Zheyuan Hu, Aaron Rovinsky, Jianlan Luo, Vikash Kumar, Abhishek Gupta, Sergey Levine Conference on Robot Learning (CoRL) 2023 arXiv \| Video
	Offline Meta-Reinforcement Learning for Industrial Insertion Tony Z. Zhao, Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Nicolas Heess, Jon Scholz, Stefan Schaal, Sergey Levine International Conference on Robotics and Automation (ICRA) 2022 arXiv \| Video \| Media Coverage
	Robust Multi-Modal Policies for Industrial Assembly via Reinforcement Learning and Demonstrations: A Large-Scale Study Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute*, Wenzhao Lian, Chang Su, Mel Vecerik, Stefan Schaal, Jon Scholz Robotics: Science and Systems (RSS) 2021 arXiv \| Video \| Media Coverage
	Action-Image Representation: Learning Scalable Deep Grasping Policies with Zero Real World Data Mohi Khansari, Daniel Kappler, Jianlan Luo, Jeff Bingham, Mrinal Kalakrishnan International Conference on Robotics and Automation (ICRA) 2020 arXiv
	Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly Jianlan Luo, Eugen Solowjow, Chengtao Wen, Juan Aparicio Ojea, Alice M Agogino, Aviv Tamar, Pieter Abbeel International Conference on Robotics and Automation (ICRA) 2019 arXiv \| Video \| Media Coverage

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	Octo: An Open-Source Generalist Robot Policy Octo Model Team ArXiv Preprint Paper \| Code
	SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning Jianlan Luo, Zheyuan Hu, Charles Xu, Siri Gadipudi, Archit Sharma, Rehaan Ahmad, Stefan Schaal, Chelsea Finn, Abhishek Gupta, Sergey Levine International Conference on Robotics and Automation (ICRA) 2024 arXiv \| Video \| Code \| Media Coverage
	FMB: A Functional Manipulation Benchmark for Generalizable Robotic Learning Jianlan Luo, Charles Xu, Fangchen Liu, Liam Tan, Zipeng Lin, Jeffrey Wu, Pieter Abbeel, Sergey Levine Under review at International Journal of Robotics Research (IJRR) arXiv \| Video \| Data
	RLIF: Interactive Imitation Learning as Reinforcement Learning Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine International Conference on Learning Representations (ICLR) 2024 arXiv \| Video \| Code \| Media Coverage 1, 2, 3, 4
	Open X-Embodiment: Robotic Learning Datasets and RT-X Models Open X-Embodiment Collaboration International Conference on Robotics and Automation (ICRA) 2024 arXiv \| Blog Post \| Dataset
	Multi-Stage Cable Routing through Hierarchical Imitation Learning Jianlan Luo, Charles Xu, Xinyang Geng, Gilbert Feng, Kuan Fang, Liam Tan, Stefan Schaal, Sergey Levine IEEE Transactions on Robotics (T-RO) 2024 arXiv \| T-RO version \| Video \| Code \| Dataset \| Data in tfds
	Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning Jianlan Luo, Perry Dong, Jeffrey Wu, Aviral Kumar, Xinyang Geng, Sergey Levine Conference on Robot Learning (CoRL) 2023 arXiv \| Code
	REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation Zheyuan Hu, Aaron Rovinsky, Jianlan Luo, Vikash Kumar, Abhishek Gupta, Sergey Levine Conference on Robot Learning (CoRL) 2023 arXiv \| Video
	Offline Meta-Reinforcement Learning for Industrial Insertion Tony Z. Zhao, Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Nicolas Heess, Jon Scholz, Stefan Schaal, Sergey Levine International Conference on Robotics and Automation (ICRA) 2022 arXiv \| Video \| Media Coverage
	Robust Multi-Modal Policies for Industrial Assembly via Reinforcement Learning and Demonstrations: A Large-Scale Study Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute*, Wenzhao Lian, Chang Su, Mel Vecerik, Stefan Schaal, Jon Scholz Robotics: Science and Systems (RSS) 2021 arXiv \| Video \| Media Coverage
	Action-Image Representation: Learning Scalable Deep Grasping Policies with Zero Real World Data Mohi Khansari, Daniel Kappler, Jianlan Luo, Jeff Bingham, Mrinal Kalakrishnan International Conference on Robotics and Automation (ICRA) 2020 arXiv
	Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly Jianlan Luo, Eugen Solowjow, Chengtao Wen, Juan Aparicio Ojea, Alice M Agogino, Aviv Tamar, Pieter Abbeel International Conference on Robotics and Automation (ICRA) 2019 arXiv \| Video \| Media Coverage

Jianlan Luo

Email: jianlanluo [at] eecs [dot] berkeley [dot] edu

Google Scholar | Twitter | GitHub

News

Research

Selected Publications [ Full List ]

Jianlan Luo Email: jianlanluo [at] eecs [dot] berkeley [dot] edu
I am a Postdoctoral Scholar at the Berkeley Artificial Intelligence Research (BAIR) Lab working with Prof. Sergey Levine. Before moving back full-time to academia in 2022, I spent two years as a researcher at Google [X] working with Prof. Stefan Schaal. I received my MS/Ph.D. from UC Berkeley in 2020. I have also spent time at Deepmind, Everyday Robots. Google Scholar \| Twitter \| GitHub