GRUtopia: Dream General Robots in a City at Scale

Fuente: arXiv
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Main Authors: Wang, Hanqing, Chen, Jiahe, Huang, Wensi, Ben, Qingwei, Wang, Tai, Mi, Boyu, Huang, Tao, Zhao, Siheng, Chen, Yilun, Yang, Sizhe, Cao, Peizhou, Yu, Wenye, Ye, Zichao, Li, Jialun, Long, Junfeng, Wang, Zirui, Wang, Huiling, Zhao, Ying, Tu, Zhongying, Qiao, Yu, Lin, Dahua, Pang, Jiangmiao
Format: Preprint
Published: 2024
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author Wang, Hanqing
Chen, Jiahe
Huang, Wensi
Ben, Qingwei
Wang, Tai
Mi, Boyu
Huang, Tao
Zhao, Siheng
Chen, Yilun
Yang, Sizhe
Cao, Peizhou
Yu, Wenye
Ye, Zichao
Li, Jialun
Long, Junfeng
Wang, Zirui
Wang, Huiling
Zhao, Ying
Tu, Zhongying
Qiao, Yu
Lin, Dahua
Pang, Jiangmiao
author_facet Wang, Hanqing
Chen, Jiahe
Huang, Wensi
Ben, Qingwei
Wang, Tai
Mi, Boyu
Huang, Tao
Zhao, Siheng
Chen, Yilun
Yang, Sizhe
Cao, Peizhou
Yu, Wenye
Ye, Zichao
Li, Jialun
Long, Junfeng
Wang, Zirui
Wang, Huiling
Zhao, Ying
Tu, Zhongying
Qiao, Yu
Lin, Dahua
Pang, Jiangmiao
contents Recent works have been exploring the scaling laws in the field of Embodied AI. Given the prohibitive costs of collecting real-world data, we believe the Simulation-to-Real (Sim2Real) paradigm is a crucial step for scaling the learning of embodied models. This paper introduces project GRUtopia, the first simulated interactive 3D society designed for various robots. It features several advancements: (a) The scene dataset, GRScenes, includes 100k interactive, finely annotated scenes, which can be freely combined into city-scale environments. In contrast to previous works mainly focusing on home, GRScenes covers 89 diverse scene categories, bridging the gap of service-oriented environments where general robots would be initially deployed. (b) GRResidents, a Large Language Model (LLM) driven Non-Player Character (NPC) system that is responsible for social interaction, task generation, and task assignment, thus simulating social scenarios for embodied AI applications. (c) The benchmark, GRBench, supports various robots but focuses on legged robots as primary agents and poses moderately challenging tasks involving Object Loco-Navigation, Social Loco-Navigation, and Loco-Manipulation. We hope that this work can alleviate the scarcity of high-quality data in this field and provide a more comprehensive assessment of Embodied AI research. The project is available at https://github.com/OpenRobotLab/GRUtopia.
format Preprint
id arxiv_https___arxiv_org_abs_2407_10943
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle GRUtopia: Dream General Robots in a City at Scale
Wang, Hanqing
Chen, Jiahe
Huang, Wensi
Ben, Qingwei
Wang, Tai
Mi, Boyu
Huang, Tao
Zhao, Siheng
Chen, Yilun
Yang, Sizhe
Cao, Peizhou
Yu, Wenye
Ye, Zichao
Li, Jialun
Long, Junfeng
Wang, Zirui
Wang, Huiling
Zhao, Ying
Tu, Zhongying
Qiao, Yu
Lin, Dahua
Pang, Jiangmiao
Robotics
Computer Vision and Pattern Recognition
Recent works have been exploring the scaling laws in the field of Embodied AI. Given the prohibitive costs of collecting real-world data, we believe the Simulation-to-Real (Sim2Real) paradigm is a crucial step for scaling the learning of embodied models. This paper introduces project GRUtopia, the first simulated interactive 3D society designed for various robots. It features several advancements: (a) The scene dataset, GRScenes, includes 100k interactive, finely annotated scenes, which can be freely combined into city-scale environments. In contrast to previous works mainly focusing on home, GRScenes covers 89 diverse scene categories, bridging the gap of service-oriented environments where general robots would be initially deployed. (b) GRResidents, a Large Language Model (LLM) driven Non-Player Character (NPC) system that is responsible for social interaction, task generation, and task assignment, thus simulating social scenarios for embodied AI applications. (c) The benchmark, GRBench, supports various robots but focuses on legged robots as primary agents and poses moderately challenging tasks involving Object Loco-Navigation, Social Loco-Navigation, and Loco-Manipulation. We hope that this work can alleviate the scarcity of high-quality data in this field and provide a more comprehensive assessment of Embodied AI research. The project is available at https://github.com/OpenRobotLab/GRUtopia.
title GRUtopia: Dream General Robots in a City at Scale
topic Robotics
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2407.10943