CRII: CSR: Energy-Aware Coordination and Management of Multi-Purpose Autonomous Robots for Maintained Continuity of Operations and Long Battery Lifetime.

CRII：CSR：多用途自主机器人的能源感知协调和管理，以保持操作的连续性和较长的电池寿命。

• 批准号: 1948365
• 负责人: Marco Brocanelli
• 金额: $ 17.5万
• 依托单位: Wayne State University
• 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
• 起止时间: 2020-02-01 至 2023-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1948365&HistoricalAwards=false
• 关键词: CRII; CSR; Energy; Aware; Coordination

Autonomous Robot (AR) fleets will soon assist humans for the execution of several tasks. One of the most important factors that will likely affect the widespread adoption of AR fleets in our society is their ease of management for the end users. The goal of this project is to achieve the easy management of the AR fleet by allowing end users to indicate the set of tasks to execute during a working period and by implementing algorithms that automatically (i) allocate tasks to ARs, (ii) coordinate recharge schedules, (iii) ensure continuity of operations, and (iv) minimize the battery degradation. The intellectual merits of this project are focused on designing an AR fleet manager system that can be used by end users to interact easily with an AR fleet. Three main research thrusts are: (i) joint optimization of concurrent tasks allocation and recharge scheduling for ARs to minimize the task downtime and battery degradation during the working period; (ii) coordination of the ARs' computing and sensing resources to balance tasks performance and energy consumption; (iii) full system implementation and experimentation on a small-scale physical testbed and a large-scale simulated testbed. The proposed work will introduce new technologies available for the management of AR fleets and boost the widespread use of autonomous robots in our society, e.g., homes, smart farms, industry, and smart cities. The project will provide a new hardware and software testbed to help train and inspire undergraduate and graduate students. New industry collaborations will be established to enhance AR adoption. New academic collaborations will also be established with researchers in various areas including robotics, artificial intelligence, control systems, sensing, and approximation algorithms. All the new algorithms and the experimental results generated as part of the proposed project will be distributed in the form of journal articles, conference proceedings, workshops, invited presentations, and student thesis. In addition, the data, source code, simulators, and hardware details will be maintained on a dedicated research website (http://brok.eng.wayne.edu/AFM.html). This repository will be retained and maintained for at least five years after the completion of the project.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.

自动机器人（AR）舰队将很快协助人类执行几项任务。可能影响AR车队在我们社会中广泛采用的最重要因素之一是最终用户的易于管理。该项目的目标是通过允许最终用户指示在工作期间要执行的任务集并通过实施自动（i）将任务分配给AR，（ii）协调充电计划，（iii）确保操作的连续性，以及（iv）最大限度地减少电池退化的算法来实现AR车队的轻松管理。该项目的智力优势集中在设计一个AR车队管理器系统，最终用户可以使用该系统轻松地与AR车队进行交互。三个主要研究方向是：（i）联合优化AR的并发任务分配和充电调度，以最大限度地减少工作期间的任务停机时间和电池退化;（ii）协调AR的计算和传感资源，以平衡任务性能和能耗;（iii）在小规模物理试验台和大规模模拟试验台上进行完整的系统实现和实验。拟议的工作将引入可用于管理AR车队的新技术，并促进自主机器人在我们社会中的广泛使用，例如，家庭、智能农场、工业和智能城市。该项目将提供一个新的硬件和软件测试平台，以帮助培训和激励本科生和研究生。将建立新的行业合作，以提高AR的采用率。新的学术合作也将建立在各个领域的研究人员，包括机器人，人工智能，控制系统，传感和近似算法。所有的新算法和实验结果作为项目的一部分，将以期刊文章，会议论文集，研讨会，邀请演讲和学生论文的形式分发。此外，数据、源代码、模拟器和硬件详细信息将保存在专用研究网站（http：//brok.eng.wayne.edu/AFM.html）上。这个储存库将在项目完成后保留和维护至少五年。这个奖项反映了NSF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。

项目成果

VECMAN: A Framework for Energy-Aware Resource Management in Vehicular Edge Computing Systems

• DOI: 10.1109/tmc.2021.3089338
• 发表时间: 2023-02
• 期刊: IEEE Transactions on Mobile Computing
• 影响因子: 7.9
• 作者: Tayebeh Bahreini;Marco Brocanelli;Daniel Grosu

Are Turn-by-Turn Navigation Systems of Regular Vehicles Ready for Edge-Assisted Autonomous Vehicles?

• DOI: 10.1109/tits.2023.3275367
• 发表时间: 2022-09
• 期刊: IEEE Transactions on Intelligent Transportation Systems
• 影响因子: 8.5
• 作者: Syeda Tanjila Atik;Marco Brocanelli;Daniel Grosu

Real-Time Schedulability Analysis for Overloaded Primary-to-Secondary Processor Systems

过载主从处理器系统的实时可调度性分析

• DOI: 10.1109/hpcc-dss-smartcity-dependsys57074.2022.00289
• 发表时间: 2022
• 期刊: Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys
• 作者: Duncan, Mitchell;Raadia, Fatima;Atik, Syeda Tanjila;Brocanelli, Marco;Fisher, Nathan
• 通讯作者: Fisher, Nathan

Towards High-Quality Battery Life for Autonomous Mobile Robot Fleets

• DOI: 10.1109/acsos55765.2022.00024
• 发表时间: 2022-09
• 期刊: 2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS)
• 作者: Akshar Shravan Chavan;Marco Brocanelli

A Maintenance-Aware Approach for Sustainable Autonomous Mobile Robot Fleet Management

可持续自主移动机器人车队管理的维护意识方法

• DOI: 10.1109/tmc.2023.3334589
• 发表时间: 2023
• 期刊: IEEE Transactions on Mobile Computing
• 影响因子: 7.9
• 作者: Atik, Syeda Tanjila;Chavan, Akshar Shravan;Grosu, Daniel;Brocanelli, Marco
• 通讯作者: Brocanelli, Marco