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09/21/2023
See to Touch: Learning Tactile Dexterity through Visual Incentives
Equipping multi-fingered robots with tactile sensing is crucial for achi...
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06/21/2023
Improving Long-Horizon Imitation Through Instruction Prediction
Complex, long-horizon planning and its combinatorial nature pose steep c...
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05/30/2023
NetHack is Hard to Hack
Neural policy learning methods have achieved remarkable results in vario...
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03/21/2023
Dexterity from Touch: Self-Supervised Pre-Training of Tactile Representations with Robotic Play
Teaching dexterity to multi-fingered robots has been a longstanding chal...
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03/02/2023
Teach a Robot to FISH: Versatile Imitation from One Minute of Demonstrations
While imitation learning provides us with an efficient toolkit to train ...
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10/18/2022
From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data
While large-scale sequence modeling from offline data has led to impress...
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10/12/2022
Holo-Dex: Teaching Dexterity with Immersive Mixed Reality
A fundamental challenge in teaching robots is to provide an effective in...
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10/11/2022
CLIP-Fields: Weakly Supervised Semantic Fields for Robotic Memory
We propose CLIP-Fields, an implicit scene model that can be trained with...
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10/03/2022
That Sounds Right: Auditory Self-Supervision for Dynamic Robot Manipulation
Learning to produce contact-rich, dynamic behaviors from raw sensory dat...
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06/30/2022
Watch and Match: Supercharging Imitation with Regularized Optimal Transport
Imitation learning holds tremendous promise in learning policies efficie...
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06/22/2022
Behavior Transformers: Cloning k modes with one stone
While behavior learning has made impressive progress in recent times, it...
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03/24/2022
Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulation
Optimizing behaviors for dexterous manipulation has been a longstanding ...
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03/21/2022
One After Another: Learning Incremental Skills for a Changing World
Reward-free, unsupervised discovery of skills is an attractive alternati...
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03/10/2022
Context is Everything: Implicit Identification for Dynamics Adaptation
Understanding environment dynamics is necessary for robots to act safely...
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01/31/2022
Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning
Recent progress in deep learning has relied on access to large and diver...
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12/02/2021
The Surprising Effectiveness of Representation Learning for Visual Imitation
While visual imitation learning offers one of the most effective ways of...
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10/28/2021
URLB: Unsupervised Reinforcement Learning Benchmark
Deep Reinforcement Learning (RL) has emerged as a powerful paradigm to s...
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07/20/2021
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning
We present DrQ-v2, a model-free reinforcement learning (RL) algorithm fo...
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07/19/2021
Playful Interactions for Representation Learning
One of the key challenges in visual imitation learning is collecting lar...
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04/07/2021
GEM: Group Enhanced Model for Learning Dynamical Control Systems
Learning the dynamics of a physical system wherein an autonomous agent o...
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03/31/2021
Simultaneous Navigation and Construction Benchmarking Environments
We need intelligent robots for mobile construction, the process of navig...
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02/25/2021
Task-Agnostic Morphology Evolution
Deep reinforcement learning primarily focuses on learning behavior, usua...
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02/22/2021
Reinforcement Learning with Prototypical Representations
Learning effective representations in image-based environments is crucia...
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12/14/2020
A Framework for Efficient Robotic Manipulation
Data-efficient learning of manipulation policies from visual observation...
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11/13/2020
Robust Policies via Mid-Level Visual Representations: An Experimental Study in Manipulation and Navigation
Vision-based robotics often separates the control loop into one module f...
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07/08/2020
Self-Supervised Policy Adaptation during Deployment
In most real world scenarios, a policy trained by reinforcement learning...
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06/17/2020
Automatic Curriculum Learning through Value Disagreement
Continually solving new, unsolved tasks is the key to learning diverse b...
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04/30/2020
Reinforcement Learning with Augmented Data
Learning from visual observations is a fundamental yet challenging probl...
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04/07/2020
State-Only Imitation Learning for Dexterous Manipulation
Dexterous manipulation has been a long-standing challenge in robotics. R...
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03/11/2020
Learning Predictive Representations for Deformable Objects Using Contrastive Estimation
Using visual model-based learning for deformable object manipulation is ...
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03/03/2020
Hierarchically Decoupled Imitation for Morphological Transfer
Learning long-range behaviors on complex high-dimensional agents is a fu...
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02/26/2020
Generalized Hindsight for Reinforcement Learning
One of the key reasons for the high sample complexity in reinforcement l...
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10/29/2019
Learning to Manipulate Deformable Objects without Demonstrations
In this paper we tackle the problem of deformable object manipulation th...
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07/26/2019
Environment Probing Interaction Policies
A key challenge in reinforcement learning (RL) is environment generaliza...
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06/19/2019
PyRobot: An Open-source Robotics Framework for Research and Benchmarking
This paper introduces PyRobot, an open-source robotics framework for res...
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03/02/2019
Robot Learning via Human Adversarial Games
Much work in robotics has focused on "human-in-the-loop" learning techni...
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10/24/2018
Sample-Efficient Learning of Nonprehensile Manipulation Policies via Physics-Based Informed State Distributions
This paper proposes a sample-efficient yet simple approach to learning c...
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10/16/2018
Multiple Interactions Made Easy (MIME): Large Scale Demonstrations Data for Imitation
In recent years, we have seen an emergence of data-driven approaches in ...
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07/18/2018
Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
Data-driven approaches to solving robotic tasks have gained a lot of tra...
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10/18/2017
Asymmetric Actor Critic for Image-Based Robot Learning
Deep reinforcement learning (RL) has proven a powerful technique in many...
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09/25/2017
Predictive-State Decoders: Encoding the Future into Recurrent Networks
Recurrent neural networks (RNNs) are a vital modeling technique that rel...
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08/04/2017
CASSL: Curriculum Accelerated Self-Supervised Learning
Recent self-supervised learning approaches focus on using a few thousand...
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03/08/2017
Robust Adversarial Reinforcement Learning
Deep neural networks coupled with fast simulation and improved computati...
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10/05/2016
Supervision via Competition: Robot Adversaries for Learning Tasks
There has been a recent paradigm shift in robotics to data-driven learni...
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09/28/2016
Learning to Push by Grasping: Using multiple tasks for effective learning
Recently, end-to-end learning frameworks are gaining prevalence in the f...
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04/05/2016