MetaUrban：面向城市微出行的具身AI仿真平台
MetaUrban: An Embodied AI Simulation Platform for Urban Micromobility
AI总结：
提出面向城市微出行的组合式仿真平台MetaUrban，通过构建无限交互式场景支持导航任务研究，实验证明环境组合特性能显著提升移动智能体的泛化能力与安全性。
摘要：
街道景观和广场等公共城市空间服务于居民，并容纳了丰富多彩的社会生活。机器人与具身AI的最新进展使得公共城市空间不再为人类所独有。送餐机器人和电动轮椅已开始与行人共享人行道，而机器狗和人形机器人最近也出现在街头。由AI驱动的、用于公共城市空间短距离出行的微出行，在未来交通系统中扮演着至关重要的角色。确保操控移动机器的AI模型具备泛化能力和安全性是必不可少的。在本研究中，我们提出了MetaUrban，一个面向AI驱动的城市微出行研究的组合式仿真平台。MetaUrban能够从组合元素构建无限数量的交互式城市场景，涵盖大量的平面图、物体放置、行人、弱势道路使用者以及其他移动智能体的外观和动力学。我们设计了点导航和社交导航任务，作为使用MetaUrban进行城市微出行研究的试点研究，并建立了强化学习和模仿学习的各种基准。我们在多种移动机器上进行了广泛评估，证明异构机械结构会显著影响AI策略的学习与执行。我们进行了彻底的消融实验，表明仿真环境的组合特性能大幅提升训练出的移动智能体的泛化能力和安全性。MetaUrban将公开发布，以提供研究机会并促进城市中安全可信的具身AI与微出行。代码和数据集将公开提供。
英文摘要：
Public urban spaces like streetscapes and plazas serve residents and accommodate social life in all its vibrant variations. Recent advances in Robotics and Embodied AI make public urban spaces no longer exclusive to humans. Food delivery bots and electric wheelchairs have started sharing sidewalks with pedestrians, while robot dogs and humanoids have recently emerged in the street. Micromobility enabled by AI for short-distance travel in public urban spaces plays a crucial component in the future transportation system. Ensuring the generalizability and safety of AI models maneuvering mobile machines is essential. In this work, we present MetaUrban, a compositional simulation platform for the AI-driven urban micromobility research. MetaUrban can construct an infinite number of interactive urban scenes from compositional elements, covering a vast array of ground plans, object placements, pedestrians, vulnerable road users, and other mobile agents' appearances and dynamics. We design point navigation and social navigation tasks as the pilot study using MetaUrban for urban micromobility research and establish various baselines of Reinforcement Learning and Imitation Learning. We conduct extensive evaluation across mobile machines, demonstrating that heterogeneous mechanical structures significantly influence the learning and execution of AI policies. We perform a thorough ablation study, showing that the compositional nature of the simulated environments can substantially improve the generalizability and safety of the trained mobile agents. MetaUrban will be made publicly available to provide research opportunities and foster safe and trustworthy embodied AI and micromobility in cities. The code and dataset will be publicly available.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
