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09/18/2023
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions
In this work, we present a scalable reinforcement learning method for tr...
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07/28/2023
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
We study how vision-language models trained on Internet-scale data can b...
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05/05/2023
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators
We describe a system for deep reinforcement learning of robotic manipula...
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03/06/2023
PaLM-E: An Embodied Multimodal Language Model
Large language models excel at a wide range of complex tasks. However, e...
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03/02/2023
Open-World Object Manipulation using Pre-trained Vision-Language Models
For robots to follow instructions from people, they must be able to conn...
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03/01/2023
Grounded Decoding: Guiding Text Generation with Grounded Models for Robot Control
Recent progress in large language models (LLMs) has demonstrated the abi...
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02/22/2023
Scaling Robot Learning with Semantically Imagined Experience
Recent advances in robot learning have shown promise in enabling robots ...
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12/13/2022
RT-1: Robotics Transformer for Real-World Control at Scale
By transferring knowledge from large, diverse, task-agnostic datasets, m...
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11/21/2022
Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models
In recent years, much progress has been made in learning robotic manipul...
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09/16/2022
Code as Policies: Language Model Programs for Embodied Control
Large language models (LLMs) trained on code completion have been shown ...
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07/26/2022
Offline Reinforcement Learning at Multiple Frequencies
Leveraging many sources of offline robot data requires grappling with th...
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07/12/2022
Inner Monologue: Embodied Reasoning through Planning with Language Models
Recent works have shown how the reasoning capabilities of Large Language...
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04/05/2022
Jump-Start Reinforcement Learning
Reinforcement learning (RL) provides a theoretical framework for continu...
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04/04/2022
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
Large language models can encode a wealth of semantic knowledge about th...
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03/29/2022
Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning
Reinforcement learning systems have the potential to enable continuous i...
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02/03/2022
How to Leverage Unlabeled Data in Offline Reinforcement Learning
Offline reinforcement learning (RL) can learn control policies from stat...
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12/17/2021
Autonomous Reinforcement Learning: Formalism and Benchmarking
Reinforcement learning (RL) provides a naturalistic framing for learning...
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11/09/2021
AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at Scale
Robotic skills can be learned via imitation learning (IL) using user-pro...
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09/16/2021
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning
Offline reinforcement learning (RL) algorithms have shown promising resu...
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07/27/2021
Persistent Reinforcement Learning via Subgoal Curricula
Reinforcement learning (RL) promises to enable autonomous acquisition of...
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04/16/2021
MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale
General-purpose robotic systems must master a large repertoire of divers...
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04/15/2021
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
We consider the problem of learning useful robotic skills from previousl...
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11/14/2020
A Geometric Perspective on Self-Supervised Policy Adaptation
One of the most challenging aspects of real-world reinforcement learning...
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06/29/2020
Confidence-rich grid mapping
Representing the environment is a fundamental task in enabling robots to...
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06/08/2020
Modeling Long-horizon Tasks as Sequential Interaction Landscapes
Complex object manipulation tasks often span over long sequences of oper...
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04/27/2020
Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning
Reinforcement learning provides a general framework for learning robotic...
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04/21/2020
Efficient Adaptation for End-to-End Vision-Based Robotic Manipulation
One of the great promises of robot learning systems is that they will be...
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04/13/2020
Thinking While Moving: Deep Reinforcement Learning with Concurrent Control
We study reinforcement learning in settings where sampling an action fro...
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01/19/2020
Gradient Surgery for Multi-Task Learning
While deep learning and deep reinforcement learning (RL) systems have de...
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10/25/2019
Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning
We present relay policy learning, a method for imitation and reinforceme...
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10/24/2019
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
Meta-reinforcement learning algorithms can enable robots to acquire new ...
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10/01/2019
Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping
The distributional perspective on reinforcement learning (RL) has given ...
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07/02/2019
Dynamics-Aware Unsupervised Discovery of Skills
Conventionally, model-based reinforcement learning (MBRL) aims to learn ...
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06/24/2019
Learning to Interactively Learn and Assist
When deploying autonomous agents in the real world, we need to think abo...
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06/24/2019
Training an Interactive Helper
Developing agents that can quickly adapt their behavior to new tasks rem...
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10/04/2018
Zero-Shot Skill Composition and Simulation-to-Real Transfer by Learning Task Representations
Simulation-to-real transfer is an important strategy for making reinforc...
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09/26/2018
Scaling simulation-to-real transfer by learning composable robot skills
We present a novel solution to the problem of simulation-to-real transfe...
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07/04/2018