{"title":"25.3基于FPGA的城市空中机动(UAM)车辆收缩模糊逻辑GOPS自主着陆制导辅助系统","authors":"Hossam O. Ahmed","doi":"10.1109/ICNS50378.2020.9222974","DOIUrl":null,"url":null,"abstract":"The importance of the Unmanned Aircraft Systems (UAS) has been increased significantly nowadays due to the increasing demands on affording novel urban transportation system solutions that could leverage the transportation utilization ratio specially in congested urban cities. However, the viability of deploying Urban Air Mobility (UAM) solutions in our daily life depends on many critical safety factors. One of the most pivotal key players in the UAM safety aspect is their capability for accurately landing on narrow and unplanned urban lading spots. Subsequently, processing the elevation sensory data by depending on a single array-based sensor unit has many drawbacks in case of sudden electronically failure or spontaneous obstacle shadowing effects. In this paper, we proposed a multicore systolic real-time processing unit that is capable to increase the automation requirement levels for future UAMs through adopting parallel and complex sensory fusion computer architectures for increasing the accuracy of UAM during the landing process. The novel Fuzzy Logic System (FLS) processing unit is interactively dealing with Multiple Sensor Nodes (MSN) that are both frequency spectrum and spatially separated on the bottom side of an UAM. The proposed idea is surpassing the conventional single sensor-array based-solutions for UAM landing process in terms of improving the accuracy and safety concerns. The proposed systolic FLS architecture in this paper has been designed and tested using MATLAB and VHDL to be interfaced with five Lidar Sensors and five ultrasonic sensors using the Intel Altera OpenVINO FPGA board. The proposed systolic FLS processing unit achieved a processing computational speed of about 25.3 Giga Operations per Seconds (GOPS) and only 178.12 mW as core dynamic thermal power dissipation.","PeriodicalId":424869,"journal":{"name":"2020 Integrated Communications Navigation and Surveillance Conference (ICNS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"25.3 GOPS Autonomous Landing Guidance Assistant System Using Systolic Fuzzy Logic System for Urban Air Mobility (UAM) Vehicles Using FPGA\",\"authors\":\"Hossam O. Ahmed\",\"doi\":\"10.1109/ICNS50378.2020.9222974\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The importance of the Unmanned Aircraft Systems (UAS) has been increased significantly nowadays due to the increasing demands on affording novel urban transportation system solutions that could leverage the transportation utilization ratio specially in congested urban cities. However, the viability of deploying Urban Air Mobility (UAM) solutions in our daily life depends on many critical safety factors. One of the most pivotal key players in the UAM safety aspect is their capability for accurately landing on narrow and unplanned urban lading spots. Subsequently, processing the elevation sensory data by depending on a single array-based sensor unit has many drawbacks in case of sudden electronically failure or spontaneous obstacle shadowing effects. In this paper, we proposed a multicore systolic real-time processing unit that is capable to increase the automation requirement levels for future UAMs through adopting parallel and complex sensory fusion computer architectures for increasing the accuracy of UAM during the landing process. The novel Fuzzy Logic System (FLS) processing unit is interactively dealing with Multiple Sensor Nodes (MSN) that are both frequency spectrum and spatially separated on the bottom side of an UAM. The proposed idea is surpassing the conventional single sensor-array based-solutions for UAM landing process in terms of improving the accuracy and safety concerns. The proposed systolic FLS architecture in this paper has been designed and tested using MATLAB and VHDL to be interfaced with five Lidar Sensors and five ultrasonic sensors using the Intel Altera OpenVINO FPGA board. The proposed systolic FLS processing unit achieved a processing computational speed of about 25.3 Giga Operations per Seconds (GOPS) and only 178.12 mW as core dynamic thermal power dissipation.\",\"PeriodicalId\":424869,\"journal\":{\"name\":\"2020 Integrated Communications Navigation and Surveillance Conference (ICNS)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Integrated Communications Navigation and Surveillance Conference (ICNS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNS50378.2020.9222974\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Integrated Communications Navigation and Surveillance Conference (ICNS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNS50378.2020.9222974","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
摘要
由于对提供新颖的城市交通系统解决方案的需求不断增加,特别是在拥挤的城市中,可以利用交通利用率,无人机系统(UAS)的重要性已经显著增加。然而,在我们的日常生活中部署城市空中交通(UAM)解决方案的可行性取决于许多关键的安全因素。UAM安全方面最关键的关键因素之一是它们在狭窄和计划外的城市提货点上准确着陆的能力。因此,在突发电子故障或自发障碍物阴影效应的情况下,依靠单个阵列传感器单元处理高程传感器数据存在许多缺点。在本文中,我们提出了一种多核收缩实时处理单元,该单元能够通过采用并行和复杂的感觉融合计算机架构来提高未来UAM的自动化要求水平,以提高UAM在着陆过程中的精度。新型模糊逻辑系统(FLS)处理单元交互式地处理位于UAM底部的多个传感器节点(MSN),这些节点在频谱和空间上都是分离的。在提高精度和安全性方面,所提出的想法超越了传统的基于单传感器阵列的UAM着陆过程解决方案。利用MATLAB和VHDL对本文提出的收缩FLS架构进行了设计和测试,并利用Intel Altera OpenVINO FPGA板与五个激光雷达传感器和五个超声波传感器进行了接口。所提出的收缩FLS处理单元的处理计算速度约为25.3 Giga Operations per Seconds (GOPS),核心动态热功耗仅为178.12 mW。
25.3 GOPS Autonomous Landing Guidance Assistant System Using Systolic Fuzzy Logic System for Urban Air Mobility (UAM) Vehicles Using FPGA
The importance of the Unmanned Aircraft Systems (UAS) has been increased significantly nowadays due to the increasing demands on affording novel urban transportation system solutions that could leverage the transportation utilization ratio specially in congested urban cities. However, the viability of deploying Urban Air Mobility (UAM) solutions in our daily life depends on many critical safety factors. One of the most pivotal key players in the UAM safety aspect is their capability for accurately landing on narrow and unplanned urban lading spots. Subsequently, processing the elevation sensory data by depending on a single array-based sensor unit has many drawbacks in case of sudden electronically failure or spontaneous obstacle shadowing effects. In this paper, we proposed a multicore systolic real-time processing unit that is capable to increase the automation requirement levels for future UAMs through adopting parallel and complex sensory fusion computer architectures for increasing the accuracy of UAM during the landing process. The novel Fuzzy Logic System (FLS) processing unit is interactively dealing with Multiple Sensor Nodes (MSN) that are both frequency spectrum and spatially separated on the bottom side of an UAM. The proposed idea is surpassing the conventional single sensor-array based-solutions for UAM landing process in terms of improving the accuracy and safety concerns. The proposed systolic FLS architecture in this paper has been designed and tested using MATLAB and VHDL to be interfaced with five Lidar Sensors and five ultrasonic sensors using the Intel Altera OpenVINO FPGA board. The proposed systolic FLS processing unit achieved a processing computational speed of about 25.3 Giga Operations per Seconds (GOPS) and only 178.12 mW as core dynamic thermal power dissipation.