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Journal Article

BEHAVIOR-1K: A Benchmark for Embodied AI with 1,000 Everyday Activities and Realistic Simulation

We present BEHAVIOR-1K, a comprehensive simulation benchmark for human-centered robotics. BEHAVIOR-1K includes two components, guided and motivated by the results of an extensive survey on "what do you want robots to do for you?". The first is the definition of 1,000 everyday activities, grounded in 50 scenes (houses, gardens, restaurants, offices, etc.) with more than 5,000 objects annotated with rich physical and semantic properties. The second is OmniGibson, a novel simulation environment that supports these activities via realistic physics simulation and rendering of rigid bodies, deformable bodies, and liquids. Our experiments indicate that the activities in BEHAVIOR-1K are long-horizon and dependent on complex manipulation skills, both of which remain a challenge for even state-of-the-art robot learning solutions. To calibrate the simulation-to-reality gap of BEHAVIOR-1K, we provide an initial study on transferring solutions learned with a mobile manipulator in a simulated apartment to its real-world counterpart. We hope that BEHAVIOR-1K's human-grounded nature, diversity, and realism make it valuable for embodied AI and robot learning research. Project website:

Chengshu Li
Ruohan Zhang
Josiah Wong
Cem Gokmen
Sanjana Srivastava
Roberto Martín-Martín
Chen Wang
Gabrael Levine
Michael Lingelbach
Jiankai Sun
Mona Anvari
Minjune Hwang
Manasi Sharma
Arman Aydin
Dhruva Bansal
Samuel Hunter
Kyu-Young Kim
Alan Lou
Caleb R Matthews
Ivan Villa-Renteria
Jerry Huayang Tang
Claire Tang
Fei Xia
Silvio Savarese
Hyowon Gweon
C. Karen Liu
Jiajun Wu
Li Fei-Fei
Journal Name
Conference on Robot Learning (CoRL), 2022
Publication Date
November 16, 2022