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20152022
most citedHow to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learned

565 citations · 4.4k across the 119 of their papers we have counts for

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56 papers · 1 filter

cs.RO20222 cited

ExAug: Robot-Conditioned Navigation Policies via Geometric Experience Augmentation

Noriaki Hirose, Dhruv Shah, Ajay Sridhar +1

Machine learning techniques rely on large and diverse datasets for generalization. Computer vision, natural language processing, and other applications can often reuse public datas…

cs.RO202217 cited

GenLoco: Generalized Locomotion Controllers for Quadrupedal Robots

Gilbert Feng, Hongbo Zhang, Zhongyu Li +8

Recent years have seen a surge in commercially-available and affordable quadrupedal robots, with many of these platforms being actively used in research and industry. As the availa…

cs.RO20222 cited

INFOrmation Prioritization through EmPOWERment in Visual Model-Based RL

Homanga Bharadhwaj, Mohammad Babaeizadeh, Dumitru Erhan +1

Model-based reinforcement learning (RL) algorithms designed for handling complex visual observations typically learn some sort of latent state representation, either explicitly or…

cs.RO2022

Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning

Abhishek Gupta, Corey Lynch, Brandon Kinman +3

Reinforcement learning systems have the potential to enable continuous improvement in unstructured environments, leveraging data collected autonomously. However, in practice these…

cs.RO2022

ASHA: Assistive Teleoperation via Human-in-the-Loop Reinforcement Learning

Sean Chen, Jensen Gao, Siddharth Reddy +3

Building assistive interfaces for controlling robots through arbitrary, high-dimensional, noisy inputs (e.g., webcam images of eye gaze) can be challenging, especially when it invo…

cs.RO202290 cited

BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning

Eric Jang, Alex Irpan, Mohi Khansari +5

In this paper, we study the problem of enabling a vision-based robotic manipulation system to generalize to novel tasks, a long-standing challenge in robot learning. We approach th…