Mrinal Kalakrishnan | DeepAI

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∙ 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...

0 Alexander Herzog, et al. ∙

∙ 04/24/2023

USA-Net: Unified Semantic and Affordance Representations for Robot Memory

In order for robots to follow open-ended instructions like "go open the ...

0 Benjamin Bolte, et al. ∙

∙ 02/04/2021

How to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learned

Deep reinforcement learning (RL) has emerged as a promising approach for...

48 Julian Ibarz, et al. ∙

∙ 05/13/2020

Action Image Representation: Learning Scalable Deep Grasping Policies with Zero Real World Data

This paper introduces Action Image, a new grasp proposal representation ...

0 Mohi Khansari, et al. ∙

∙ 10/01/2019

Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping

The distributional perspective on reinforcement learning (RL) has given ...

1 Cristian Bodnar, et al. ∙

∙ 06/07/2019

Watch, Try, Learn: Meta-Learning from Demonstrations and Reward

Imitation learning allows agents to learn complex behaviors from demonst...

1 Allan Zhou, et al. ∙

∙ 04/15/2019

Learning Probabilistic Multi-Modal Actor Models for Vision-Based Robotic Grasping

Many previous works approach vision-based robotic grasping by training a...

0 Mengyuan Yan, et al. ∙

∙ 12/18/2018

Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks

Real world data, especially in the domain of robotics, is notoriously co...

8 Stephen James, et al. ∙

∙ 06/27/2018

QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation

In this paper, we study the problem of learning vision-based dynamic man...

0 Dmitry Kalashnikov, et al. ∙

∙ 10/17/2017

Multi-task Domain Adaptation for Deep Learning of Instance Grasping from Simulation

Learning-based approaches to robotic manipulation are limited by the sca...

0 Kuan Fang, et al. ∙

∙ 09/22/2017

Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping

Instrumenting and collecting annotated visual grasping datasets to train...

0 Konstantinos Bousmalis, et al. ∙

∙ 10/03/2016

Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search

In principle, reinforcement learning and policy search methods can enabl...

0 Ali Yahya, et al. ∙

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