News

[Jun 2026] We released τ₀-WM , a unified video-action world model for robotic manipulation.
[May 2026] We introduced Learning while Deploying (LWD) , a fleet-scale reinforcement learning framework for continually improving generalist robot policies through real-world deployment.
[Aug 2025] HIL-SERL appeared in Science Robotics and was featured on the journal cover.
[May 2025] I was named to the MIT Innovators Under 35 (China) list.

Research

My research focuses on building scalable and reliable robot learning systems that can operate, adapt, and continually improve in the physical world. Rather than treating pretraining, post-training, and deployment as separate stages, I aim to connect them into a unified learning loop that integrates vision-language-action policies, world models, real-world reinforcement learning, and scalable robotic infrastructure.

A central goal of my work is to enable robots to learn from heterogeneous multimodal experience, anticipate the physical consequences of their actions, improve through real-world interaction, and feed deployment experience back into subsequent training. Key research themes include:

Robot Foundation Models — Developing vision-language-action policies and world models that enable compositional task understanding, predictive planning, and generalization across tasks, objects, environments, and robot embodiments.
Real-World Post-Training — Designing sample-efficient reinforcement learning and human-in-the-loop systems that improve pretrained policies through physical interaction, enabling high reliability and precision in contact-rich manipulation.
Scalable Robotic Learning Systems — Building open-source and fleet-scale learning frameworks that connect data collection, training, evaluation, deployment, and continual improvement in real robotic systems.

Selected Publications [ Full List ]

	τ₀-WM: A Unified Video-Action World Model for Robotic Manipulation Pengfei Zhou, Shengcong Chen, Di Chen, Jiaxu Wang, Rongjun Jin, Bingwen Zhu, Yike Pan, Songen Gu, Kuanning Wang, Shufeng Nan, Xingyu Qiu, Chenhao Qiu, Pu Yang, Yunuo Cai, Jianxiong Gao, Yifan Li, Yanwei Fu, Xiangyu Yue, Zhi Chen, Jianlan Luo ArXiv Paper
	Learning While Deploying: Fleet-Scale Reinforcement Learning for Generalist Robot Policies Yi Wang, Xinchen Li, Pengwei Xie, Pu Yang, Buqing Nie, Yunuo Cai, Qinglin Zhang, Chendi Qu, Jeffrey Wu, Jianheng Song, Xinlin Ren, Jingshun Huang, Mingjie Pan, Siyuan Feng, Zhi Chen, Jianlan Luo ArXiv Paper
	SOP: A Scalable Online Post-Training System for Vision-Language-Action Models Mingjie Pan, Siyuan Feng, Qinglin Zhang, Xinchen Li, Jianheng Song, Chendi Qu, Yi Wang, Chuankang Li, Ziyu Xiong, Zhi Chen, Yi Liu, Jianlan Luo ArXiv Paper
	Unified Embodied VLM Reasoning with Robotic Action via Autoregressive Discretized Pre-training Yi Liu, Sukai Wang, Dafeng Wei, Xiaowei Cai, Linqing Zhong, Jiange Yang, Guanghui Ren, Jinyu Zhang, Maoqing Yao, Chuankang Li, Xindong He, Liliang Chen, Jianlan Luo ArXiv Paper
	Act2Goal: From World Model to General Goal-conditioned Policy Pengfei Zhou, Liliang Chen, Shengcong Chen, Di Chen, Wenzhi Zhao, Rongjun Jin， Guanghui Ren, Jianlan Luo Robotics: Science and Systems (RSS) 2026 Paper
	Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning Jianlan Luo, Charles Xu, Jeffrey Wu, Sergey Levine Science Robotics 2025 Paper \| Code \| UC Berkeley News \| Tech Xplore
	Reflective Planning: Vision-Language Models for Multi-Stage Long-Horizon Robotic Manipulation Yunhai Feng, Jiaming Han, Zhuoran Yang, Xiangyu Yue, Sergey Levine, Jianlan Luo Conference on Robot Learning (CoRL) 2025 Paper \| Code
	RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning Charles Xu, Qiyang Li, Jianlan Luo, Sergey Levine Robotics: Science and Systems (RSS) 2025 Paper \| Code
	Yell At Your Robot: Improving On-the-Fly from Language Corrections Lucy Xiaoyang Shi, Zheyuan Hu, Tony Z. Zhao, Archit Sharma, Karl Pertsch, Jianlan Luo, Sergey Levine, Chelsea Finn Robotics: Science and Systems (RSS) 2024 Paper \| Code
	Octo: An Open-Source Generalist Robot Policy Octo Model Team Robotics: Science and Systems (RSS) 2024 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 International Journal of Robotics Research (IJRR) 2024 arXiv \| IJRR Version \| 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 Best Conference Paper Award 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
	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
	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

	τ₀-WM: A Unified Video-Action World Model for Robotic Manipulation Pengfei Zhou, Shengcong Chen, Di Chen, Jiaxu Wang, Rongjun Jin, Bingwen Zhu, Yike Pan, Songen Gu, Kuanning Wang, Shufeng Nan, Xingyu Qiu, Chenhao Qiu, Pu Yang, Yunuo Cai, Jianxiong Gao, Yifan Li, Yanwei Fu, Xiangyu Yue, Zhi Chen, Jianlan Luo ArXiv Paper
	Learning While Deploying: Fleet-Scale Reinforcement Learning for Generalist Robot Policies Yi Wang, Xinchen Li, Pengwei Xie, Pu Yang, Buqing Nie, Yunuo Cai, Qinglin Zhang, Chendi Qu, Jeffrey Wu, Jianheng Song, Xinlin Ren, Jingshun Huang, Mingjie Pan, Siyuan Feng, Zhi Chen, Jianlan Luo ArXiv Paper
	SOP: A Scalable Online Post-Training System for Vision-Language-Action Models Mingjie Pan, Siyuan Feng, Qinglin Zhang, Xinchen Li, Jianheng Song, Chendi Qu, Yi Wang, Chuankang Li, Ziyu Xiong, Zhi Chen, Yi Liu, Jianlan Luo ArXiv Paper
	Unified Embodied VLM Reasoning with Robotic Action via Autoregressive Discretized Pre-training Yi Liu, Sukai Wang, Dafeng Wei, Xiaowei Cai, Linqing Zhong, Jiange Yang, Guanghui Ren, Jinyu Zhang, Maoqing Yao, Chuankang Li, Xindong He, Liliang Chen, Jianlan Luo ArXiv Paper
	Act2Goal: From World Model to General Goal-conditioned Policy Pengfei Zhou, Liliang Chen, Shengcong Chen, Di Chen, Wenzhi Zhao, Rongjun Jin， Guanghui Ren, Jianlan Luo Robotics: Science and Systems (RSS) 2026 Paper
	Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning Jianlan Luo, Charles Xu, Jeffrey Wu, Sergey Levine Science Robotics 2025 Paper \| Code \| UC Berkeley News \| Tech Xplore
	Reflective Planning: Vision-Language Models for Multi-Stage Long-Horizon Robotic Manipulation Yunhai Feng, Jiaming Han, Zhuoran Yang, Xiangyu Yue, Sergey Levine, Jianlan Luo Conference on Robot Learning (CoRL) 2025 Paper \| Code
	RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning Charles Xu, Qiyang Li, Jianlan Luo, Sergey Levine Robotics: Science and Systems (RSS) 2025 Paper \| Code
	Yell At Your Robot: Improving On-the-Fly from Language Corrections Lucy Xiaoyang Shi, Zheyuan Hu, Tony Z. Zhao, Archit Sharma, Karl Pertsch, Jianlan Luo, Sergey Levine, Chelsea Finn Robotics: Science and Systems (RSS) 2024 Paper \| Code
	Octo: An Open-Source Generalist Robot Policy Octo Model Team Robotics: Science and Systems (RSS) 2024 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 International Journal of Robotics Research (IJRR) 2024 arXiv \| IJRR Version \| 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 Best Conference Paper Award 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
	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
	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

News

Research

Selected Publications [ Full List ]