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

no code implementations • 14 Mar 2024 • Chengshu Li, Ruohan Zhang, Josiah Wong, Cem Gokmen, Sanjana Srivastava, Roberto Martín-Martín, Chen Wang, Gabrael Levine, Wensi Ai, Benjamin Martinez, Hang Yin, Michael Lingelbach, Minjune Hwang, Ayano Hiranaka, Sujay Garlanka, Arman Aydin, Sharon Lee, Jiankai Sun, Mona Anvari, Manasi Sharma, Dhruva Bansal, Samuel Hunter, Kyu-Young Kim, Alan Lou, Caleb R Matthews, Ivan Villa-Renteria, Jerry Huayang Tang, Claire Tang, Fei Xia, Yunzhu Li, Silvio Savarese, Hyowon Gweon, C. Karen Liu, Jiajun Wu, Li Fei-Fei

We present BEHAVIOR-1K, a comprehensive simulation benchmark for human-centered robotics.

Error-Aware Imitation Learning from Teleoperation Data for Mobile Manipulation

no code implementations • 9 Dec 2021 • Josiah Wong, Albert Tung, Andrey Kurenkov, Ajay Mandlekar, Li Fei-Fei, Silvio Savarese, Roberto Martín-Martín

Doing this is challenging for two reasons: on the data side, current interfaces make collecting high-quality human demonstrations difficult, and on the learning side, policies trained on limited data can suffer from covariate shift when deployed.

Imitation Learning Navigate

OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation

1 code implementation • 2 Oct 2021 • Josiah Wong, Viktor Makoviychuk, Anima Anandkumar, Yuke Zhu

Operational Space Control (OSC) has been used as an effective task-space controller for manipulation.

Robot Manipulation

What Matters in Learning from Offline Human Demonstrations for Robot Manipulation

1 code implementation • 6 Aug 2021 • Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, Roberto Martín-Martín

Based on the study, we derive a series of lessons including the sensitivity to different algorithmic design choices, the dependence on the quality of the demonstrations, and the variability based on the stopping criteria due to the different objectives in training and evaluation.

Imitation Learning reinforcement-learning +2

Learning Multi-Arm Manipulation Through Collaborative Teleoperation

no code implementations • 12 Dec 2020 • Albert Tung, Josiah Wong, Ajay Mandlekar, Roberto Martín-Martín, Yuke Zhu, Li Fei-Fei, Silvio Savarese

To address these challenges, we present Multi-Arm RoboTurk (MART), a multi-user data collection platform that allows multiple remote users to simultaneously teleoperate a set of robotic arms and collect demonstrations for multi-arm tasks.

Imitation Learning

IGibson 1.0: a Simulation Environment for Interactive Tasks in Large Realistic Scenes

2 code implementations • 5 Dec 2020 • Bokui Shen, Fei Xia, Chengshu Li, Roberto Martín-Martín, Linxi Fan, Guanzhi Wang, Claudia Pérez-D'Arpino, Shyamal Buch, Sanjana Srivastava, Lyne P. Tchapmi, Micael E. Tchapmi, Kent Vainio, Josiah Wong, Li Fei-Fei, Silvio Savarese

We present iGibson 1. 0, a novel simulation environment to develop robotic solutions for interactive tasks in large-scale realistic scenes.

Imitation Learning

robosuite: A Modular Simulation Framework and Benchmark for Robot Learning

6 code implementations • 25 Sep 2020 • Yuke Zhu, Josiah Wong, Ajay Mandlekar, Roberto Martín-Martín, Abhishek Joshi, Soroush Nasiriany, Yifeng Zhu

robosuite is a simulation framework for robot learning powered by the MuJoCo physics engine.

Gesture Generation