524 citations · 1.6k across the 16 of their papers we have counts for
4 papers · 1 filter
Grasp2Vec: Learning Object Representations from Self-Supervised Grasping
Eric Jang, Coline Devin, Vincent Vanhoucke +1
Well structured visual representations can make robot learning faster and can improve generalization. In this paper, we study how we can acquire effective object-centric representa…
QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation
Dmitry Kalashnikov, Alex Irpan, Peter Pastor +8
In this paper, we study the problem of learning vision-based dynamic manipulation skills using a scalable reinforcement learning approach. We study this problem in the context of g…
Sim-to-Real: Learning Agile Locomotion For Quadruped Robots
Jie Tan, Tingnan Zhang, Erwin Coumans +5
Designing agile locomotion for quadruped robots often requires extensive expertise and tedious manual tuning. In this paper, we present a system to automate this process by leverag…
Classification of crystallization outcomes using deep convolutional neural networks
Andrew E. Bruno, Patrick Charbonneau, Janet Newman +6
The Machine Recognition of Crystallization Outcomes (MARCO) initiative has assembled roughly half a million annotated images of macromolecular crystallization experiments from vari…