课题基金 / 基金详情

CPS: Small: Collaborative Research: RUI: Towards Efficient and Secure Agricultural Information Collection Using a Multi-Robot System

CPS: Small: Collaborative Research: RUI: Towards Efficient and Secure Agricultural Information Collection Using a Multi-Robot System
CPS:小型:协作研究:RUI:使用多机器人系统实现高效、安全的农业信息收集
批准号:
1932300
负责人:
Ayan Dutta
金额:
$36.47万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-03-01 至 2025-02-28

项目摘要

项目成果

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中文摘要
翻译
随着世界人口的增长和农业用地的减少,必须通过保护作物健康和防治病虫害来最大限度地提高作物产量。尽管几十年前的做法仍然存在,但所谓的精准农业解决方案也得到了越来越多的采用,这种解决方案在日常农田运营中采用了传感、自动化和分析方面的新兴技术。随着农民获得关键数据(如土地和天气状况)的实时访问权,并能迅速与他人分享任何不利的发现,农田运营正在演变成成熟的网络物理系统。为此,本项目寻求开发、实施和评估一个自主、高效和安全的多机器人农业信息收集系统。该项目由北佛罗里达大学(UNF)领导,并得到中佛罗里达大学(UCF)的支持,有两个主要目标:(i)开发和实施自主移动机器人的新型信息收集技术,这些机器人使用区块链以高效而安全的方式收集、存储和共享数据;(ii)培训本科生和研究生进行基础和应用研究,同时与佛罗里达州东北部的当地农田合作伙伴密切合作。目前的技术已经将机器人用于农业用途,但它们通常具有很高的维护成本,并且不一定考虑与安全和数据完整性相关的问题。主要目标是设计和部署一组自主机器人,这些机器人可以进行无线通信,并在规划的路径上导航,以收集有价值的数据。该项目还将考虑安全攻击的威胁,收集的数据可能会被破坏;寻求新的基于分布式区块链的共识协议,以减轻此类攻击的敌对影响。该项目还包含一个重要的研究和教育组成部分,利用UNF在主要本科机构(RUI)背景下的领导作用。作为一个主要的本科机构,在杰克逊维尔地区缺乏追求更高学位的机会。该项目与UNF和UCF之间建立的谅解备忘录(MoU)保持一致,为计算机/工程专业的学生提供一个在UNF攻读硕士学位的渠道,这些硕士学位可以无缝地进入UCF的博士课程。学生们将受益于将在UNF开发的新机器人课程和UCF提供的课程。研究进展将通过每年在这两个机构举行的技术研讨会来展示。开发的解决方案有望转移到其他网络物理系统应用,包括搜索和救援、巡逻、先进制造等。最广泛地说,这个项目将提高当今青少年和年轻人对即将到来的农业危机的认识,如果世界粮食生产进一步无法满足日益增长的全球人口的需求。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
With the growing world population and diminishing agricultural lands, it becomes imperative to maximize crop yield by protecting crop health and mitigating against pests and diseases. Though there are decades-old practices still in place, there is also growing adoption of so-called precision agriculture solutions, which employ emerging technologies in sensing, automation, and analytics in daily farmland operations. As farmers gain real-time access to critical data (e.g., land and weather conditions) and can quickly share any untoward findings with others, farmland operations are morphing into full-fledged cyber-physical systems. To this end, this project seeks to develop, implement and evaluate a multi-robot agricultural information collection system that is autonomous, efficient and secure.This project led by the University of North Florida (UNF) and supported by the University of Central Florida (UCF) has two main goals: (i) develop and implement novel information collection techniques for autonomous mobile robots that collect, store and share data in an efficient yet secure manner using blockchain,and (ii)and to train undergraduate and graduate students to conduct basic and applied research while closely working with local farmland partners in north-east Florida. Current technologies already use robots for agricultural purposes, but they typically have a high maintenance cost and do not necessarily consider issues related to security and data integrity. The primary objective is to design and deploy a set of autonomous robots that communicate wirelessly and navigate through planned paths in order to collect valuable data. This project will also consider the threat of security attacks by which collected data can be corrupted; seeking new distributed blockchain-based consensus protocols that mitigate the adversarial influence of such attacks. This project also contains a significant research and education component leveraging the leadership of UNF in the context of a primarily undergraduate institution (RUI). Being predominantly an undergraduate institution, there is a lack of opportunity for pursuing higher degrees in the Jacksonville area. This project aligns with an established Memorandum of Understanding (MoU) between UNF and UCF to provide a conduit for computing/engineering students to pursue M.S. degrees at UNF that feed seamlessly into Ph.D. programs at UCF. Students will benefit from the new robotics course to be developed at UNF and the ones being offered at UCF. Research progress will be showcased via technical workshops at both institutions to be held annually. Developed solutions are expected to transfer to other cyber-physical system applications, including search and rescue, patrolling, advanced manufacturing, among others. Most broadly, this project will raise awareness among today's teenagers and young adults of the impending agricultural crisis if worldwide food production falls even further behind meeting demands of an increasing global population.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.
期刊论文(7)
专著(0)
科研奖励(0)
会议论文
Multi-robot Information Sampling Using Deep Mean Field Reinforcement Learning
使用深度平均场强化学习的多机器人信息采样
DOI: 10.1109/smc52423.2021.9658795
发表时间: 2021
期刊: and Cybernetics (SMC
影响因子: --
作者: [Said, Tuffa, Wolbert, Jeffery, Khodadadeh, Siavash, Dutta, Ayan, Kreidl, O. Patrick, Boloni, Ladislau, Roy, Swapnoneel]
通讯作者: Roy, Swapnoneel
Secure Multi-Robot Information Sampling with Periodic and Opportunistic Connectivity
通过定期和机会性连接进行安全多机器人信息采样
DOI: 10.1109/icra46639.2022.9812211
发表时间: 2022
期刊: 2022 International Conference on Robotics and Automation (ICRA
影响因子: --
作者: [Samman, Tamim, Dutta, Ayan, Kreidl, O. Patrick, Roy, Swapnoneel, Boloni, Ladislau]
通讯作者: Boloni, Ladislau
DOI: 10.1109/tnsm.2022.3219494
发表时间: 2022-12
期刊: IEEE Transactions on Network and Service Management
影响因子: 5.3
作者: [Cesar Castellon Escobar;Swapnoneel Roy;O. P. Kreidl;Ayan Dutta;Ladislau Bölöni]
通讯作者: Cesar Castellon Escobar;Swapnoneel Roy;O. P. Kreidl;Ayan Dutta;Ladislau Bölöni
Secure Multi-Robot Adaptive Information Sampling
安全多机器人自适应信息采样
DOI: 10.1109/ssrr53300.2021.9597867
发表时间: 2021
期刊: and Rescue Robotics (SSRR
影响因子: --
作者: [Samman, Tamim, Spearman, James, Dutta, Ayan, Kreidl, O. Patrick, Roy, Swapnoneel, Boloni, Ladislau]
通讯作者: Boloni, Ladislau
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