Collaborative Research: Frameworks: Simulating Autonomous Agents and the Human-Autonomous Agent Interaction

协作研究：框架：模拟自主代理和人机交互

• 批准号: 2209794
• 负责人: Chris Schwarz
• 金额: $ 20.51万
• 依托单位: University of Iowa
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2209794&HistoricalAwards=false
• 关键词: Collaborative; Research; Frameworks; Simulating; Autonomous

This project augments the Chrono computer simulation platform in transformative ways. Chrono's purpose is to predict through simulation the interplay between mechatronic systems, the environment they operate in, and humans with whom they might interact. The open-source simulation platform is slated to become a community-shared virtual investigation tool used to probe competing engineering designs and test hypotheses that would be too dangerous, difficult, or costly to verify through physical experiments. Chrono has been and will continue to be used in multiple fields and disciplines, e.g., terramechanics, astrophysics; soft matter physics; biomechanics; mechanical engineering; civil engineering; industrial engineering; and computer science. Specifically, it is used to engineer the 2023 VIPER lunar rover; relied upon by US Army experts in evaluating its wheeled and tracked vehicle designs; used in the US and Germany in the wind turbine industry; and involved in designing wave energy conversion solutions in Europe. Upon project completion, Chrono will become a simulation engine in Gazebo, which is widely used in robotics research; operate on the largest driving simulator in the US; empower research in the bio-robotics and field-robotics communities; and assist efforts in the broad area of automotive research carried out by a consortium of universities and companies under the umbrella of the Automotive Research Center. The educational impact of this project is threefold: training undergraduate, graduate, and post-doctoral students in a multi-disciplinary fashion that emphasizes advanced computing skills development; anchoring two new courses in autonomous vehicle control and simulation in robotics; and broadening participation in computing through a residential program on the campus of the University of Wisconsin-Madison that engages teachers and students from rural high-schools. Innovation and discovery are fueled by quality data. At its core, this project seeks to increase the share of this data that has simulation as its provenance. In this context, a multi-disciplinary team of 40 researchers augments and validates a physics-based simulation framework that empowers research in autonomous agents (AAs). The AAs operate in complex and unstructured dynamic environments and might engage in two-way interaction with humans or other AAs. This project enables Chrono to generate machine learning training data quickly and inexpensively; facilitates comparison of competing designs for assessing trade-offs; and gauges candidate design robustness via testing in simulation of corner-case scenarios. These tasks are accomplished by upgrading and extending Chrono to leverage recent computational dynamics innovations, e.g., a faster index 3 differential algebraic equations solver; a new approach to solving frictional contact problems; a real-time solver for handling flexible-body dynamics in soft robotics via nonlinear finite element analysis; a best-in-class simulator for terradynamics applications; reliance on just-in-time compiling for producing executables that are both problem- and hardware-optimized; a novel way for using mixed data representations for parsimonious storing of state information; and a scalable multi-agent framework that enables geographically-distributed, over the Internet, real-time simulation of human-AA interaction.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目以变革性的方式增强了计算机模拟平台。 Chrono的目的是通过模拟机电系统，他们操作的环境以及与之相互作用的人类之间的相互作用进行预测。开源模拟平台计划成为一种社区共享的虚拟调查工具，用于探究竞争性的工程设计和测试假设，这些假设太危险，困难或昂贵，无法通过物理实验进行验证。 Chrono曾经并将继续在多个领域和学科中使用，例如地形力学，天体物理学；软物质物理；生物力学；机械工业;土木工程;工业工程；和计算机科学。具体而言，它用于设计2023 Viper Lunar Rover；美国陆军专家依靠评估其车轮和追踪车辆设计；在美国和德国在风力涡轮机业中使用；并参与设计欧洲的波能量转换解决方案。项目完成后，Chrono将成为凉亭的模拟引擎，该引擎广泛用于机器人研究中。在美国最大的驾驶模拟器上操作；赋予生物机器人和现场机器人社区中的研究；并协助在汽车研究中心的伞下，由大学和公司联盟进行的汽车研究广泛领域的努力。该项目的教育影响是三倍：以多学科的方式培训本科生，研究生和博士后学生，强调高级计算技能的发展；在自动驾驶汽车控制和模拟机器人技术中锚定了两个新课程；并通过威斯康星大学麦迪逊分校校园的住宅计划扩大了计算的参与，该计划吸引了来自农村高中生的教师和学生。创新和发现是由质量数据推动的。从本质上讲，该项目旨在增加具有模拟作为出处的数据的份额。在这种情况下，由40位研究人员组成的多学科团队增加了基于物理的模拟框架，该框架赋予了自主代理（AAS）研究的能力。 AAS在复杂且非结构化的动态环境中运行，并可能与人类或其他AA进行双向互动。该项目使Chrono能够快速，廉价地生成机器学习培训数据；促进比较竞争设计以评估权衡；并通过测试在角落场景的模拟中测试来衡量候选人设计鲁棒性。这些任务是通过升级和扩展Chrono来利用最近的计算动力学创新来完成的，例如，更快的索引3差分代数方程求解器；解决摩擦接触问题的新方法；通过非线性有限元分析来处理软机器人中柔性动力学的实时求解器；用于Terradyanic应用的一流模拟器；依靠及时编译用于生产问题和硬件优化的可执行文件；使用混合数据表示的一种新颖的方式来存储状态信息；以及一个可扩展的多机构框架，可以通过互联网上的地理分配，对人类AA互动进行实时模拟。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛影响的审查标准通过评估来通过评估来获得支持的。