research
∙
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...
share
research
∙
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...
research
∙
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...
research
∙
03/06/2023
PaLM-E: An Embodied Multimodal Language Model
Large language models excel at a wide range of complex tasks. However, e...
research
∙
12/13/2022
RT-1: Robotics Transformer for Real-World Control at Scale
By transferring knowledge from large, diverse, task-agnostic datasets, m...
research
∙
11/02/2022
Dual Generator Offline Reinforcement Learning
In offline RL, constraining the learned policy to remain close to the da...
research
∙
11/02/2022
Offline RL With Realistic Datasets: Heteroskedasticity and Support Constraints
Offline reinforcement learning (RL) learns policies entirely from static...
research
∙
07/12/2022
Inner Monologue: Embodied Reasoning through Planning with Language Models
Recent works have shown how the reasoning capabilities of Large Language...
research
∙
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...
research
∙
02/03/2022
How to Leverage Unlabeled Data in Offline Reinforcement Learning
Offline reinforcement learning (RL) can learn control policies from stat...
research
∙
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...
research
∙
09/16/2021
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning
Offline reinforcement learning (RL) algorithms have shown promising resu...
research
∙
04/16/2021
MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale
General-purpose robotic systems must master a large repertoire of divers...
research
∙
04/15/2021
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
We consider the problem of learning useful robotic skills from previousl...
research
∙
03/26/2021
Visionary: Vision architecture discovery for robot learning
We propose a vision-based architecture search algorithm for robot manipu...
research
∙
06/29/2020
Supervised Learning and Reinforcement Learning of Feedback Models for Reactive Behaviors: Tactile Feedback Testbed
Robots need to be able to adapt to unexpected changes in the environment...
research
∙
06/12/2019
Meta-Learning via Learned Loss
We present a meta-learning approach based on learning an adaptive, high-...
research
∙
11/08/2018
Learning Latent Space Dynamics for Tactile Servoing
In order to achieve a dexterous robotic manipulation, we need to equip o...
research
∙
10/12/2018
Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience
We consider the problem of transferring policies to the real world by tr...
research
∙
10/03/2016
