Youngwoon Lee | DeepAI

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∙ 08/31/2023

Language-Conditioned Path Planning

Contact is at the core of robotic manipulation. At times, it is desired ...

0 Amber Xie, et al. ∙

∙ 05/23/2023

Video Prediction Models as Rewards for Reinforcement Learning

Specifying reward signals that allow agents to learn complex behaviors i...

4 Alejandro Escontrela, et al. ∙

∙ 05/22/2023

FurnitureBench: Reproducible Real-World Benchmark for Long-Horizon Complex Manipulation

Reinforcement learning (RL), imitation learning (IL), and task and motio...

0 Minho Heo, et al. ∙

∙ 02/10/2023

Controllability-Aware Unsupervised Skill Discovery

One of the key capabilities of intelligent agents is the ability to disc...

0 Seohong Park, et al. ∙

∙ 12/09/2022

PATO: Policy Assisted TeleOperation for Scalable Robot Data Collection

Large-scale data is an essential component of machine learning as demons...

0 Shivin Dass, et al. ∙

∙ 07/15/2022

Skill-based Model-based Reinforcement Learning

Model-based reinforcement learning (RL) is a sample-efficient way of lea...

0 Lucy Xiaoyang Shi, et al. ∙

∙ 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...

9 Youngwoon Lee, et al. ∙

∙ 11/11/2021

Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation

Learning complex manipulation tasks in realistic, obstructed environment...

0 I-Chun Arthur Liu, et al. ∙

∙ 07/21/2021

Demonstration-Guided Reinforcement Learning with Learned Skills

Demonstration-guided reinforcement learning (RL) is a promising approach...

0 Karl Pertsch, et al. ∙

∙ 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...

0 Grace Zhang, et al. ∙

∙ 10/22/2020

Accelerating Reinforcement Learning with Learned Skill Priors

Intelligent agents rely heavily on prior experience when learning a new ...

0 Karl Pertsch, et al. ∙

∙ 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...

9 Jun Yamada, et al. ∙

∙ 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...

0 Youngwoon Lee, et al. ∙

∙ 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...

16 Youngwoon Lee, et al. ∙

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