title: GRUtopia: Dream General Robots in a City at Scale
summary: 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.
paper_authors._id: 669606b85e5e72a43406f888
paper_authors.name: Hanqing Wang
paper_authors._id: 669606b85e5e72a43406f889
paper_authors.name: Jiahe Chen
paper_authors._id: 669606b85e5e72a43406f88a
paper_authors.name: Wensi Huang
paper_authors._id: 669606b85e5e72a43406f88b
paper_authors.name: Qingwei Ben
paper_authors._id: 669606b85e5e72a43406f88c
paper_authors.name: Tai Wang
paper_authors._id: 669606b85e5e72a43406f88d
paper_authors.name: Boyu Mi
paper_authors._id: 669606b85e5e72a43406f88e
paper_authors.name: Tao Huang
paper_authors._id: 669606b85e5e72a43406f88f
paper_authors.name: Siheng Zhao
paper_authors._id: 669606b85e5e72a43406f890
paper_authors.name: Yilun Chen
paper_authors._id: 669606b85e5e72a43406f891
paper_authors.name: Sizhe Yang
paper_authors._id: 669606b85e5e72a43406f892
paper_authors.name: Peizhou Cao
paper_authors._id: 669606b85e5e72a43406f893
paper_authors.name: Wenye Yu
paper_authors._id: 669606b85e5e72a43406f894
paper_authors.name: Zichao Ye
paper_authors._id: 669606b85e5e72a43406f895
paper_authors.name: Jialun Li
paper_authors._id: 669606b85e5e72a43406f896
paper_authors.name: Junfeng Long
paper_authors._id: 669606b85e5e72a43406f897
paper_authors.name: Zirui Wang
paper_authors._id: 669606b85e5e72a43406f898
paper_authors.name: Huiling Wang
paper_authors._id: 669606b85e5e72a43406f899
paper_authors.name: Ying Zhao
paper_authors._id: 669606b85e5e72a43406f89a
paper_authors.name: Zhongying Tu
paper_authors._id: 669606b85e5e72a43406f89b
paper_authors.name: Yu Qiao
paper_authors._id: 669606b85e5e72a43406f89c
paper_authors.name: Dahua Lin
paper_authors._id: 669606b85e5e72a43406f89d
paper_authors.name: Jiangmiao Pang
paper_title: GRUtopia: Dream General Robots in a City at Scale
paper_summary: 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.
paper_ai_summary: Project GRUtopia introduces GRScenes, GRResidents, and GRBench to simulate a comprehensive 3D interactive society for embodied AI, focusing on diverse environments and advanced robotic tasks.
paper_ai_keywords: Sim2Real Embodied AI interactive 3D society GRScenes scene dataset Large Language Model (LLM) Non-Player Character (NPC) GRResidents GRBench legged robots Object Loco-Navigation Social Loco-Navigation Loco-Manipulation