CCSS: Autonomous Drone and Ground Robot Cooperative Tasking in Complex Indoor Environments

CCSS：复杂室内环境中的自主无人机和地面机器人协作任务

• 批准号: 1923163
• 负责人: Shiwen Mao
• 金额: $ 39.89万
• 依托单位: Auburn University
• 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: 2019-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1923163&HistoricalAwards=false
• 关键词: CCSS; Autonomous; Drone; Ground; Robot

The requirements for automated inventory and precise location of items have become vital to modern supply chain management. The objective of this project is to create an innovative ground robot-drone network system, which consists of a group of autonomous ground robots and drones, to provide inventory counts and precise locations of passive radio-frequency identification (pRFID) tagged items in highly complex environments, such as warehouses, retail stores, hazmat storage facilities, or factories. This project will significantly improve the state-of-the-art of supply chain management and Internet of Things (IoT) systems, and provide a significant step forward to fully harvest the potential of the proposed robotic-drone platform. The project's education plan includes developing and enhancing various undergraduate and graduate-level courses. Graduate and undergraduate students will be exposed to the state-of-the-art techniques, and gain hands-on experience in the cutting-edge technology that is at the very frontier of modern communications, circuits, and sensing systems (CCSS). Outcomes from this project will be disseminated through technical publications, conference presentations, a project website, and at the bi-annual Wireless Engineering Research and Education Center (WEREC) and RFID Lab meetings. The team is fully committed to promoting participation from under-represented groups in research, and will continue such efforts via outreach, e.g., through the NSF REU and RET programs and collaboration with HBCUs.The pRFID technology has been widely deployed in the past decade for serialized item level identification and data sharing. However, most pRFID technology implementations utilize fixed reader points, or human operated handheld scanners, and cannot provide precise item location. The demand of logistics visibility requires automated inventory and the precise location information of items. In the proposed research, the autonomous ground robot-drone network system combined with a precise RFID localization method will bridge the above gap. By deploying cooperative ground robots and drones, mounted with commercial off-the-shelf pRFID equipment, to provide automated inventory and precise location of pRFID tagged items. The framework cooperates heterogeneous individual items into a coherent system for more complex task that is not possible for any individual item. The proposed architecture will also provide an innovative communication, control, and computing framework for general IoT systems. The framework will be disclosed as open-source tools to boost relevant research in the CCSS community. The following thrusts will be accomplished in this project. (i) Ground robot and drone network architecture: the architecture will be developed to provide communication, computing, and control for the ground robot and drone to cooperatively operate for generic tasks. It also provides the fundamental methods for the ground robot and drone to pair with each other to form a symbiotic system. (ii) Ground robot and drone indoor navigation: a ground robot enhanced mechanism will be introduced to enable drone(s) to precisely localize itself in the complex indoor environment. When the localization goals are achieved, a method will be investigate to enable the drone(s) and ground robot to safely and efficiently navigate in an object-rich and confined space environment. (iii) Accurate inventory counts and precise localization of pRFIDs: the ground robot-drone network will be prototyped to operate pRFID inventory and provide precise location of pRFID tagged items. (iv) This project also includes a thorough integration and assessment plan, to test the proposed ground robot-drone integrated system in real warehouse and retail store environments.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.

自动库存和项目的确切位置的要求对于现代供应链管理至关重要。该项目的目的是创建一个创新的地面机器人无人机网络系统，该系统由一组自主地面机器人和无人机组成，以提供库存计数和被动式射频标识（PRFID）标记的项目的精确位置，这些项目在高度复杂的环境中，例如仓库，零售店，Hazmat存储设施，或者是范围的存储设施。该项目将显着改善供应链管理和物联网（IoT）系统的最新技术，并为充分收获拟议的机器人无人机平台的潜力提供了重要的一步。该项目的教育计划包括开发和增强各种本科和研究生级课程。研究生和本科生将接触到最先进的技术，并在现代通信，电路和传感系统（CCSS）的前沿技术方面获得动手经验。该项目的成果将通过技术出版物，会议演示，项目网站以及两年一次的无线工程研究和教育中心（WEREC）和RFID实验室会议传播。该团队完全致力于促进代表性不足的研究团体的参与，并将通过宣传来继续进行此类努力，例如，通过NSF REU和RET计划以及与HBCUS的合作。PRFID技术在过去十年中已广泛部署，用于串行的项目级别识别和数据共享。但是，大多数PRFID技术实施都使用固定的读取器或人类操作的手持式扫描仪，并且无法提供精确的物品位置。物流可见性的需求需要自动库存和项目的确切位置信息。在拟议的研究中，自主地面机器人无人机网络系统与精确的RFID定位方法相结合将弥合上述差距。通过部署配有商业现成的PRFID设备安装的合作地面机器人和无人机，以提供自动化的库存和PRFID标记项目的精确位置。该框架将异质的单个项目合作成一个连贯的系统，以进行更复杂的任务，这对于任何单个项目都是不可能的。所提出的架构还将为一般物联网系统提供创新的通信，控制和计算框架。该框架将作为开源工具披露，以促进CCSS社区的相关研究。该项目将完成以下推力。 （i）地面机器人和无人机网络体系结构：将开发架构，以为地面机器人和无人机提供通信，计算和控制，以合作进行通用任务。它还为地面机器人和无人机提供了基本方法，可以彼此配对以形成共生系统。 （ii）地面机器人和无人机室内导航：将引入地面机器人增强机制，以使无人机能够精确地定位于复杂的室内环境中。当实现本地化目标时，将研究一种方法，以使无人机和地面机器人能够安全有效地在物体富含对象且受限的空间环境中导航。 （iii）PRFID的准确库存计数和精确定位：将原型型机器人无线电网络进行原型运行PRFID库存，并提供PRFID标记项目的精确位置。 （iv）该项目还包括一个彻底的集成和评估计划，以测试真正的仓库和零售商店环境中提议的地面机器人无线电集成系统。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来通过评估来进行评估的。

项目成果

MulTLoc: RF Hologram Tensor Filtering and Upscaling for Locating Multiple RFID Tags

• DOI: 10.1109/icccn52240.2021.9522256
• 发表时间: 2021-07
• 期刊: 2021 International Conference on Computer Communications and Networks (ICCCN)
• 作者: Xiangyu Wang;Jian Zhang;S. Mao;Senthilkumar C. G. Periaswamy;J. Patton

Indoor Fingerprinting With Bimodal CSI Tensors: A Deep Residual Sharing Learning Approach

• DOI: 10.1109/jiot.2020.3026608
• 发表时间: 2021-03
• 期刊: IEEE Internet of Things Journal
• 影响因子: 10.6
• 作者: Xiangyu Wang;Xuyu Wang;S. Mao

On Remote Temperature Sensing Using Commercial UHF RFID Tags

• DOI: 10.1109/jiot.2019.2941023
• 发表时间: 2019-12-01
• 期刊: IEEE INTERNET OF THINGS JOURNAL
• 影响因子: 10.6
• 作者: Wang, Xiangyu;Zhang, Jian;Patton, Justin
• 通讯作者: Patton, Justin

DEEP CONVOLUTIONAL GAUSSIAN PROCESSES FOR MMWAVE OUTDOOR LOCALIZATION

• DOI: 10.1109/icassp39728.2021.9414388
• 发表时间: 2021-01-01
• 期刊: 2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021)
• 作者: Wang, Xuyu;Patil, Mohini;Patel, Palak Anilkumar
• 通讯作者: Patel, Palak Anilkumar

Temperature Forecasting for Stored Grain: A Deep Spatiotemporal Attention Approach

• DOI: 10.1109/jiot.2021.3078332
• 发表时间: 2021-12-01
• 期刊: IEEE INTERNET OF THINGS JOURNAL
• 影响因子: 10.6
• 作者: Duan, Shanshan;Yang, Weidong;Zhang, Yuan
• 通讯作者: Zhang, Yuan