Lerrel Pinto

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Carnegie Mellon University

Generalized Hindsight for Reinforcement Learning

One of the key reasons for the high sample complexity in reinforcement l...
02/26/2020 ∙ by Alexander C. Li, et al. ∙ 26 ∙ share

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Learning Predictive Representations for Deformable Objects Using Contrastive Estimation

Using visual model-based learning for deformable object manipulation is ...
03/11/2020 ∙ by Wilson Yan, et al. ∙ 13 ∙ share

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Reinforcement Learning with Augmented Data

Learning from visual observations is a fundamental yet challenging probl...
04/30/2020 ∙ by Michael Laskin, et al. ∙ 12 ∙ share

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Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias

Data-driven approaches to solving robotic tasks have gained a lot of tra...
07/18/2018 ∙ by Abhinav Gupta, et al. ∙ 10 ∙ share

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Learning to Manipulate Deformable Objects without Demonstrations

In this paper we tackle the problem of deformable object manipulation th...
10/29/2019 ∙ by Yilin Wu, et al. ∙ 10 ∙ share

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Hierarchically Decoupled Imitation for Morphological Transfer

Learning long-range behaviors on complex high-dimensional agents is a fu...
03/03/2020 ∙ by Donald J. Hejna III, et al. ∙ 10 ∙ share

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Automatic Curriculum Learning through Value Disagreement

Continually solving new, unsolved tasks is the key to learning diverse b...
06/17/2020 ∙ by Yunzhi Zhang, et al. ∙ 10 ∙ share

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PyRobot: An Open-source Robotics Framework for Research and Benchmarking

This paper introduces PyRobot, an open-source robotics framework for res...
06/19/2019 ∙ by Adithyavairavan Murali, et al. ∙ 9 ∙ share

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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...
10/24/2018 ∙ by Lerrel Pinto, et al. ∙ 2 ∙ share

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State-Only Imitation Learning for Dexterous Manipulation

Dexterous manipulation has been a long-standing challenge in robotics. R...
04/07/2020 ∙ by Ilija Radosavovic, et al. ∙ 1 ∙ share

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Predictive-State Decoders: Encoding the Future into Recurrent Networks

Recurrent neural networks (RNNs) are a vital modeling technique that rel...
09/25/2017 ∙ by Arun Venkatraman, et al. ∙ 0 ∙ share

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CASSL: Curriculum Accelerated Self-Supervised Learning

Recent self-supervised learning approaches focus on using a few thousand...
08/04/2017 ∙ by Adithyavairavan Murali, et al. ∙ 0 ∙ share

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Supervision via Competition: Robot Adversaries for Learning Tasks

There has been a recent paradigm shift in robotics to data-driven learni...
10/05/2016 ∙ by Lerrel Pinto, et al. ∙ 0 ∙ share

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Learning to Push by Grasping: Using multiple tasks for effective learning

Recently, end-to-end learning frameworks are gaining prevalence in the f...
09/28/2016 ∙ by Lerrel Pinto, et al. ∙ 0 ∙ share

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The Curious Robot: Learning Visual Representations via Physical Interactions

What is the right supervisory signal to train visual representations? Cu...
04/05/2016 ∙ by Lerrel Pinto, et al. ∙ 0 ∙ share

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Asymmetric Actor Critic for Image-Based Robot Learning

Deep reinforcement learning (RL) has proven a powerful technique in many...
10/18/2017 ∙ by Lerrel Pinto, et al. ∙ 0 ∙ share

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Robust Adversarial Reinforcement Learning

Deep neural networks coupled with fast simulation and improved computati...
03/08/2017 ∙ by Lerrel Pinto, et al. ∙ 0 ∙ share

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Multiple Interactions Made Easy (MIME): Large Scale Demonstrations Data for Imitation

In recent years, we have seen an emergence of data-driven approaches in ...
10/16/2018 ∙ by Pratyusha Sharma, et al. ∙ 0 ∙ share

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Robot Learning via Human Adversarial Games

Much work in robotics has focused on "human-in-the-loop" learning techni...
03/02/2019 ∙ by Jiali Duan, et al. ∙ 0 ∙ share

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Environment Probing Interaction Policies

A key challenge in reinforcement learning (RL) is environment generaliza...
07/26/2019 ∙ by Wenxuan Zhou, et al. ∙ 0 ∙ share

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Lerrel Pinto

Featured Co-authors

Pieter Abbeel

Jitendra Malik

Abhinav Gupta

C. -C. Jay Kuo

Qian Wang

Byron Boots

Xiaolong Wang

Martial Hebert

J Andrew Bagnell

Tao Chen

Rahul Sukthankar

Generalized Hindsight for Reinforcement Learning

Learning Predictive Representations for Deformable Objects Using Contrastive Estimation

Reinforcement Learning with Augmented Data

Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias

Learning to Manipulate Deformable Objects without Demonstrations

Hierarchically Decoupled Imitation for Morphological Transfer

Automatic Curriculum Learning through Value Disagreement

PyRobot: An Open-source Robotics Framework for Research and Benchmarking

Sample-Efficient Learning of Nonprehensile Manipulation Policies via Physics-Based Informed State Distributions

State-Only Imitation Learning for Dexterous Manipulation

Predictive-State Decoders: Encoding the Future into Recurrent Networks

CASSL: Curriculum Accelerated Self-Supervised Learning

Supervision via Competition: Robot Adversaries for Learning Tasks

Learning to Push by Grasping: Using multiple tasks for effective learning

The Curious Robot: Learning Visual Representations via Physical Interactions

Asymmetric Actor Critic for Image-Based Robot Learning

Robust Adversarial Reinforcement Learning

Multiple Interactions Made Easy (MIME): Large Scale Demonstrations Data for Imitation

Robot Learning via Human Adversarial Games

Environment Probing Interaction Policies