Elements:Open-source hardware and software evaluation system for UAV

要素：无人机开源软硬件评估系统

• 批准号: 2103951
• 负责人: Hyesoon Kim
• 金额: $ 60万
• 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: 2021
• 资助国家: 美国
• 起止时间: 2021-06-15 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2103951&HistoricalAwards=false
• 关键词: Elements; Open; source; hardware; software

The usage of Robots and Unmanned Aerial Vehicles (UAVs) is increasing, and they are becoming a part of our everyday lives. In the process, robotic systems have ceased to be solely a mechanical design problem but now include substantial computing power as well. However, little system or architecture research has been done for robotics workloads, especially in realistic environments. The existing infrastructure is focused on drone flight algorithm tests, with little flexibility to configure the computing capability. To this end, this project develops a software-hardware co-design framework that includes an end-to-end, vertically integrated stack that enables reconfigurable hardware to be programmed and exposed to virtual reality environments for realistic drone navigation problems. It will establish a flexible software-hardware infrastructure of drones and open up exciting possibilities for more research in academia and industry. Since drones are nowadays widely used, the research has potential for impact across a wide range of applications. The project develops an end-to-end hardware and software infrastructure that can evaluate the computing requirements and test out new architectures and technologies. This includes: (1) profiling the workload for UAVs, which include both model-based as well as learning-based workloads; (2) developing an open-source hardware/software drone platform that can be used for testing computing architecture/systems with a real system; (3) developing a cyber-physical system infrastructure that can be connected with drones and flight simulation; and (4) developing a simulation infrastructure to offload high-end computation to other accelerators while running drone flight scenarios. The project will advance the state of the art in implementation of processors for robotics/UAV workloads. It will offer new opportunities in power-constrained platforms for applications including surveillance, automotive, environment, military, and disaster to name a few.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.

机器人和无人机(UAVs)的使用越来越多，它们正成为我们日常生活的一部分。在这个过程中，机器人系统不再仅仅是一个机械设计问题，而是现在也包括了大量的计算能力。然而，针对机器人工作负载的系统或体系结构研究很少，尤其是在现实环境中。现有的基础设施专注于无人机飞行算法测试，配置计算能力的灵活性很小。为此，该项目开发了一个软硬件协同设计框架，其中包括一个端到端、垂直集成的堆栈，该堆栈使可重新配置的硬件能够被编程并暴露在虚拟现实环境中，以解决现实的无人机导航问题。它将建立灵活的无人机软硬件基础设施，并为学术界和工业界开展更多研究开辟令人兴奋的可能性。由于无人机现在被广泛使用，这项研究可能会对广泛的应用产生影响。该项目开发了一个端到端的硬件和软件基础设施，可以评估计算需求并测试新的架构和技术。这包括：(1)分析无人机的工作负载，其中包括基于模型的工作负载以及基于学习的工作负载；(2)开发一个开源硬件/软件无人机平台，该平台可用于用真实系统测试计算架构/系统；(3)开发一个能够与无人机和飞行模拟连接的网络物理系统基础设施；以及(4)开发一个模拟基础设施，在运行无人机飞行场景的同时将高端计算负载转移到其他加速器。该项目将推动机器人/无人机工作负载处理器的实施。它将在电力受限的平台上提供新的机会，应用包括监控、汽车、环境、军事和灾难等。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

An Energy-Efficient and Runtime-Reconfigurable FPGA-Based Accelerator for Robotic Localization Systems

用于机器人定位系统的节能且运行时可重构的基于 FPGA 的加速器

• DOI: 10.1109/cicc53496.2022.9772870
• 发表时间: 2022
• 期刊: IEEE Custom Integrated Circuits Conference (CICC
• 作者: Liu, Qiang;Wan, Zishen;Yu, Bo;Liu, Weizhuang;Liu, Shaoshan;Raychowdhury, Arijit
• 通讯作者: Raychowdhury, Arijit