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06/20/2023
SPRINT: Scalable Policy Pre-Training via Language Instruction Relabeling
Pre-training robot policies with a rich set of skills can substantially ...
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05/22/2023
FurnitureBench: Reproducible Real-World Benchmark for Long-Horizon Complex Manipulation
Reinforcement learning (RL), imitation learning (IL), and task and motio...
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03/09/2023
Hierarchical Neural Program Synthesis
Program synthesis aims to automatically construct human-readable program...
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12/09/2022
PATO: Policy Assisted TeleOperation for Scalable Robot Data Collection
Large-scale data is an essential component of machine learning as demons...
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07/15/2022
Skill-based Model-based Reinforcement Learning
Model-based reinforcement learning (RL) is a sample-efficient way of lea...
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04/25/2022
Skill-based Meta-Reinforcement Learning
While deep reinforcement learning methods have shown impressive results ...
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04/25/2022
Task-Induced Representation Learning
In this work, we evaluate the effectiveness of representation learning a...
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11/15/2021
Adversarial Skill Chaining for Long-Horizon Robot Manipulation via Terminal State Regularization
Skill chaining is a promising approach for synthesizing complex behavior...
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11/11/2021
Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation
Learning complex manipulation tasks in realistic, obstructed environment...
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08/31/2021
Learning to Synthesize Programs as Interpretable and Generalizable Policies
Recently, deep reinforcement learning (DRL) methods have achieved impres...
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07/21/2021
Demonstration-Guided Reinforcement Learning with Learned Skills
Demonstration-guided reinforcement learning (RL) is a promising approach...
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07/01/2021
Policy Transfer across Visual and Dynamics Domain Gaps via Iterative Grounding
The ability to transfer a policy from one environment to another is a pr...
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10/22/2020
Accelerating Reinforcement Learning with Learned Skill Priors
Intelligent agents rely heavily on prior experience when learning a new ...
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10/22/2020
Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments
Deep reinforcement learning (RL) agents are able to learn contact-rich m...
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12/16/2019
To Follow or not to Follow: Selective Imitation Learning from Observations
Learning from demonstrations is a useful way to transfer a skill from on...
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11/17/2019
IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
The IKEA Furniture Assembly Environment is one of the first benchmarks f...
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10/30/2019
Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation
Model-agnostic meta-learners aim to acquire meta-learned parameters from...
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12/18/2018
Toward Multimodal Model-Agnostic Meta-Learning
Gradient-based meta-learners such as MAML are able to learn a meta-prior...
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09/29/2018
Auto-conditioned Recurrent Mixture Density Networks for Complex Trajectory Generation
Recent advancements in machine learning research have given rise to recu...
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04/03/2018
3D Interpreter Networks for Viewer-Centered Wireframe Modeling
Understanding 3D object structure from a single image is an important bu...
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03/07/2017
Unsupervised Visual-Linguistic Reference Resolution in Instructional Videos
We propose an unsupervised method for reference resolution in instructio...
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09/16/2016