113 citations · 918 across the 43 of their papers we have counts for
26 papers · 1 filter
Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation
Suraj Nair, Eric Mitchell, Kevin Chen +3
We study the problem of learning a range of vision-based manipulation tasks from a large offline dataset of robot interaction. In order to accomplish this, humans need easy and eff…
What Matters in Learning from Offline Human Demonstrations for Robot Manipulation
Ajay Mandlekar, Danfei Xu, Josiah Wong +7
Imitating human demonstrations is a promising approach to endow robots with various manipulation capabilities. While recent advances have been made in imitation learning and batch…
BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments
Sanjana Srivastava, Chengshu Li, Michael Lingelbach +11
We introduce BEHAVIOR, a benchmark for embodied AI with 100 activities in simulation, spanning a range of everyday household chores such as cleaning, maintenance, and food preparat…
iGibson 2.0: Object-Centric Simulation for Robot Learning of Everyday Household Tasks
Chengshu Li, Fei Xia, Roberto Martín-Martín +13
Recent research in embodied AI has been boosted by the use of simulation environments to develop and train robot learning approaches. However, the use of simulation has skewed the…
Discovering Generalizable Skills via Automated Generation of Diverse Tasks
Kuan Fang, Yuke Zhu, Silvio Savarese +1
The learning efficiency and generalization ability of an intelligent agent can be greatly improved by utilizing a useful set of skills. However, the design of robot skills can ofte…
LASER: Learning a Latent Action Space for Efficient Reinforcement Learning
Arthur Allshire, Roberto Martín-Martín, Charles Lin +3
The process of learning a manipulation task depends strongly on the action space used for exploration: posed in the incorrect action space, solving a task with reinforcement learni…