演示RFUniverse:嵌入式AI的多物理场仿真平台

Haoyuan Fu, Wenqiang Xu, Ruolin Ye, Han Xue, Zhenjun Yu, Tutian Tang, Yutong Li, Wenxin Du, Jieyi Zhang, Cewu Lu
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引用次数: 4

摘要

多物理场现象,即涉及物理定律不同方面的耦合效应,在现实世界中普遍存在,并且在执行日常家务时经常会遇到。寻求协助或取代人类劳动者的智能代理将需要学会在家务环境中应对这种现象。为了使智能体具备这种能力,研究界需要一个仿真环境,该环境将有能力作为这些智能体训练过程的试验台,并具有支持多物理场耦合效应的能力。虽然工业生产中已经采用了许多成熟的多物理场仿真软件,但这些技术尚未应用于机器人学习或体现人工智能的研究。为了弥补这一差距,我们提出了一个名为RFUniverse的新型仿真环境。该模拟器不仅可以计算刚体动力学和多体动力学,还可以计算日常生活中常见的多物理场耦合效应,如气固相互作用、流固相互作用、传热等。由于该模拟器具有独特的多物理场能力,我们可以在将其部署到现实世界之前,在模拟环境中对涉及多物理场耦合效应的复杂动态的任务进行基准测试。RFUniverse提供了多个接口,让用户以各种方式与虚拟世界进行交互,这对于学习、计划和控制非常有用和必要。我们用强化学习测试了三个任务,包括切食物、推水和抓毛巾。我们还用一个经典的计划控制范式来评估黄油的推动。该模拟器在多物理场耦合效应的计算方面提供了物理模拟的增强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Demonstrating RFUniverse: A Multiphysics Simulation Platform for Embodied AI
Multiphysics phenomena, the coupling effects involving different aspects of physics laws, are pervasive in the real world and can often be encountered when performing everyday household tasks. Intelligent agents which seek to assist or replace human laborers will need to learn to cope with such phenomena in household task settings. To equip the agents with such kind of abilities, the research community needs a simulation environment, which will have the capability to serve as the testbed for the training process of these intelligent agents, to have the ability to support multiphysics coupling effects. Though many mature simulation software for multiphysics simulation have been adopted in industrial production, such techniques have not been applied to robot learning or embodied AI research. To bridge the gap, we propose a novel simulation environment named RFUniverse. This simulator can not only compute rigid and multi-body dynamics, but also multiphysics coupling effects commonly observed in daily life, such as air-solid interaction, fluid-solid interaction, and heat transfer. Because of the unique multiphysics capacities of this simulator, we can benchmark tasks that involve complex dynamics due to multiphysics coupling effects in a simulation environment before deploying to the real world. RFUniverse provides multiple interfaces to let the users interact with the virtual world in various ways, which is helpful and essential for learning, planning, and control. We benchmark three tasks with reinforcement learning, including food cutting, water pushing, and towel catching. We also evaluate butter pushing with a classic planning-control paradigm. This simulator offers an enhancement of physics simulation in terms of the computation of multiphysics coupling effects.
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