2.4k citations · 8.4k across the 129 of their papers we have counts for
15 papers · 1 filter
Error-Aware Imitation Learning from Teleoperation Data for Mobile Manipulation
Josiah Wong, Albert Tung, Andrey Kurenkov +4
In mobile manipulation (MM), robots can both navigate within and interact with their environment and are thus able to complete many more tasks than robots only capable of navigatio…
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…
Merlion: A Machine Learning Library for Time Series
Aadyot Bhatnagar, Paul Kassianik, Chenghao Liu +20
We introduce Merlion, an open-source machine learning library for time series. It features a unified interface for many commonly used models and datasets for anomaly detection and…
Sample-Efficient Safety Assurances using Conformal Prediction
Rachel Luo, Shengjia Zhao, Jonathan Kuck +4
When deploying machine learning models in high-stakes robotics applications, the ability to detect unsafe situations is crucial. Early warning systems can provide alerts when an un…
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…
Co-GAIL: Learning Diverse Strategies for Human-Robot Collaboration
Chen Wang, Claudia Pérez-D'Arpino, Danfei Xu +3
We present a method for learning a human-robot collaboration policy from human-human collaboration demonstrations. An effective robot assistant must learn to handle diverse human b…
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…
JRDB-Act: A Large-scale Dataset for Spatio-temporal Action, Social Group and Activity Detection
Mahsa Ehsanpour, Fatemeh Saleh, Silvio Savarese +2
The availability of large-scale video action understanding datasets has facilitated advances in the interpretation of visual scenes containing people. However, learning to recognis…
TRiPOD: Human Trajectory and Pose Dynamics Forecasting in the Wild
Vida Adeli, Mahsa Ehsanpour, Ian Reid +4
Joint forecasting of human trajectory and pose dynamics is a fundamental building block of various applications ranging from robotics and autonomous driving to surveillance systems…
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…
Generalization Through Hand-Eye Coordination: An Action Space for Learning Spatially-Invariant Visuomotor Control
Chen Wang, Rui Wang, Ajay Mandlekar +3
Imitation Learning (IL) is an effective framework to learn visuomotor skills from offline demonstration data. However, IL methods often fail to generalize to new scene configuratio…
Embodied Intelligence via Learning and Evolution
Agrim Gupta, Silvio Savarese, Surya Ganguli +1
The intertwined processes of learning and evolution in complex environmental niches have resulted in a remarkable diversity of morphological forms. Moreover, many aspects of animal…
Local Calibration: Metrics and Recalibration
Rachel Luo, Aadyot Bhatnagar, Yu Bai +7
Probabilistic classifiers output confidence scores along with their predictions, and these confidence scores should be calibrated, i.e., they should reflect the reliability of the…