S&AS: INT: COLLAB: Aerodynamic Intelligent Morphing System (A-IMS) for Autonomous Smart Utility Truck Safety and Productivity in Severe Environments

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• 批准号: 1849198
• 负责人: Kyriakos G Vamvoudakis
• 金额: $ 32.5万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1849198&HistoricalAwards=false
• 关键词: S& INT; COLLAB; Aerodynamic; Intelligent

Utility trucks are the first responders in areas of extreme weather situations for tasks such as rescuing people from disaster areas, cutting trees to restore traffic, and repairing electric posts and restoring power. This study establishes a scientific framework for maintaining the productivity and safety of emergency response vehicles while eliminating accidents. This is implemented via a novel integrated framework to monitor and predict weather conditions and feed that information into intelligent mechanisms that autonomously shape the aerodynamic surfaces of utility trucks. The project includes recruitment efforts and activities to integrate high-school students, as well as students from multiple cultures, and disciplines into autonomy research. This project is expected to contribute new scientific knowledge and engineering techniques for next generation transportation infrastructure resiliency, and to facilitate economic growth in the state of Alabama.Unlike conventional approaches, the A-IMS will integrate model-free shape-morphing learning mechanisms with model-based interactive design to manage air-fluid flows, based on the road conditions, meteorology, speed limit, wind speed, and direction. This potentially transformative framework for A-IMS will: (1) bring new perspectives of learning to enhance the adaptability and intelligence in natural-engineering systems that leverage physical and information processes; (2) establish an integrated design framework for hazardous environments to achieve resilience, and productivity through integrated adaptation of morphological properties while also mitigating the effects of potentially adversarial learning agents that can exist in the cloud; (3) investigate the interactive physical components of the A-IMS, that will simultaneously operate in two different mediums of multi-phase fluids, and solids (i.e., the air/fluid and road). The A-IMS framework will be evaluated through hardware/software implementation, as well as in real-world conditions in the unique test conditions available at Wall of Wind at Florida International University. The project's education and outreach component include integrated research and education plans that will lead to technology transfer and summer camps with a special focus on reaching out to underrepresented minorities and women.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.

多用途卡车是极端天气状况地区的第一批响应人员，任务包括从灾区营救人们，砍伐树木以恢复交通，修复电线杆和恢复电力。这项研究为在消除事故的同时保持应急车辆的生产力和安全性建立了一个科学的框架。这是通过一个新颖的集成框架来实现的，该框架可以监测和预测天气状况，并将这些信息输入到智能机制中，这些机制可以自动塑造多功能卡车的空气动力学表面。该项目包括将高中生以及来自不同文化和学科的学生纳入自主研究的招聘努力和活动。该项目有望为下一代交通基础设施的弹性提供新的科学知识和工程技术，并促进阿拉巴马州的经济增长。与传统方法不同，A-IMS将基于路况、气象、限速、风速和方向，将无模型形状变形学习机制与基于模型的交互设计相结合，以管理空气-流体流动。A-IMS的这一潜在的变革性框架将：(1)带来新的学习视角，以增强利用物理和信息过程的自然工程系统的适应性和智能性；(2)建立危险环境的综合设计框架，通过对形态特性的综合适应，实现弹性和生产力，同时还减轻可能存在于云中的潜在对抗性学习试剂的影响；(3)研究A-IMS的交互物理组件，它将同时在多相流体和固体(即，空气/流体和道路)两种不同介质中运行。A-IMS框架将通过硬件/软件实施以及在佛罗里达国际大学风墙所提供的独特测试条件下的真实世界条件进行评估。该项目的教育和推广部分包括综合研究和教育计划，这些计划将导致技术转让和夏令营，特别侧重于接触未被充分代表的少数民族和妇女。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Hamiltonian-Driven Hybrid Adaptive Dynamic Programming

哈密​​顿驱动的混合自适应动态规划

• DOI: 10.1109/tsmc.2019.2962103
• 发表时间: 2020-01
• 期刊: IEEE Transactions on Systems, Man, and Cybernetics: Systems
• 作者: Yongliang Yang;Kyriakos G. Vamvoudakis;Hamidreza Modares;Yixin Yin;Donald C. Wunsch
• 通讯作者: Donald C. Wunsch

Synchronous Reinforcement Learning-Based Control for Cognitive Autonomy

基于同步强化学习的认知自主控制

• DOI: 10.1561/2600000022
• 发表时间: 2020
• 期刊: Foundations and Trends® in Systems and Control
• 作者: Vamvoudakis, Kyriakos G.;Kokolakis, Nick-Marios T.
• 通讯作者: Kokolakis, Nick-Marios T.

Recursive Reasoning for Bounded Rationality in Multi-Agent Non-Equilibrium Play Learning Systems

多智能体非平衡博弈学习系统中有限理性的递归推理

• DOI: 10.1109/ccta48906.2021.9658965
• 发表时间: 2021
• 期刊: 2021 IEEE Conference on Control Technology and Applications (CCTA
• 作者: Fotiadis, Filippos;Vamvoudakis, Kyriakos G.
• 通讯作者: Vamvoudakis, Kyriakos G.

Non-Equilibrium Learning in Stochastic Games

随机博弈中的非平衡学习

• DOI: 10.23919/acc55779.2023.10156061
• 发表时间: 2023
• 期刊: 2023 American Control Conference (ACC
• 作者: Vamvoudakis, Kyriakos G.

Hamiltonian-Driven Adaptive Dynamic Programming With Approximation Errors

具有近似误差的哈密顿驱动自适应动态规划

• DOI: 10.1109/tcyb.2021.3108034
• 发表时间: 2022
• 期刊: IEEE Transactions on Cybernetics
• 影响因子: 11.8
• 作者: Yongliang Yang;Hamidreza Modares;Kyriakos G. Vamvoudakis;Wei He;Cheng-Zhong Xu;Donald C. Wunsch
• 通讯作者: Donald C. Wunsch