用于有效载荷运输的人工智能无人机

Reem Alshanbari, S. Khan, Nazek El‐atab, Muhammad Mustafa Hussain
{"title":"用于有效载荷运输的人工智能无人机","authors":"Reem Alshanbari, S. Khan, Nazek El‐atab, Muhammad Mustafa Hussain","doi":"10.1109/NAECON46414.2019.9058320","DOIUrl":null,"url":null,"abstract":"Recently unmanned aerial vehicles (UAV) have received a growing attention due to their wide range of applications. Here, we demonstrate UAVs with artificial intelligence (AI) capabilities for application in autonomous payload transport. An algorithm is developed for target detection with multiple phases on the ground, which once the target is detected, would trigger the release of the payload that is attached on the drone. The experimental results show that the average frame rate over x seconds achieved a 19.4010717352 fps (frame per second) detection speed. Releasing the payload is achieved using a 3D printed system based on rack and pinion gears. In addition, auto flight program is developed to enable the autonomous movement of the drone. As a proof-of-concept, a small drone known as \"Phantom DJI\" is used for .6 kg autonomous payload transport along a predefined route to a target location.","PeriodicalId":193529,"journal":{"name":"2019 IEEE National Aerospace and Electronics Conference (NAECON)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"AI Powered Unmanned Aerial Vehicle for Payload Transport Application\",\"authors\":\"Reem Alshanbari, S. Khan, Nazek El‐atab, Muhammad Mustafa Hussain\",\"doi\":\"10.1109/NAECON46414.2019.9058320\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently unmanned aerial vehicles (UAV) have received a growing attention due to their wide range of applications. Here, we demonstrate UAVs with artificial intelligence (AI) capabilities for application in autonomous payload transport. An algorithm is developed for target detection with multiple phases on the ground, which once the target is detected, would trigger the release of the payload that is attached on the drone. The experimental results show that the average frame rate over x seconds achieved a 19.4010717352 fps (frame per second) detection speed. Releasing the payload is achieved using a 3D printed system based on rack and pinion gears. In addition, auto flight program is developed to enable the autonomous movement of the drone. As a proof-of-concept, a small drone known as \\\"Phantom DJI\\\" is used for .6 kg autonomous payload transport along a predefined route to a target location.\",\"PeriodicalId\":193529,\"journal\":{\"name\":\"2019 IEEE National Aerospace and Electronics Conference (NAECON)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE National Aerospace and Electronics Conference (NAECON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAECON46414.2019.9058320\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE National Aerospace and Electronics Conference (NAECON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAECON46414.2019.9058320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

近年来,无人驾驶飞行器(UAV)因其广泛的应用受到越来越多的关注。在这里,我们展示了具有人工智能(AI)功能的无人机在自主有效载荷运输中的应用。开发了在地面上进行多阶段目标探测的算法,一旦探测到目标,就会触发释放附着在无人机上的有效载荷。实验结果表明,x秒内的平均帧率达到19.4010717352 fps(帧/秒)的检测速度。释放有效载荷是使用基于齿条和小齿轮的3D打印系统实现的。此外,还开发了自动飞行程序,使无人机能够自主移动。作为概念验证,一架名为“幻影大疆”(Phantom DJI)的小型无人机将沿着预定路线自动运送0.6公斤的有效载荷到目标位置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
AI Powered Unmanned Aerial Vehicle for Payload Transport Application
Recently unmanned aerial vehicles (UAV) have received a growing attention due to their wide range of applications. Here, we demonstrate UAVs with artificial intelligence (AI) capabilities for application in autonomous payload transport. An algorithm is developed for target detection with multiple phases on the ground, which once the target is detected, would trigger the release of the payload that is attached on the drone. The experimental results show that the average frame rate over x seconds achieved a 19.4010717352 fps (frame per second) detection speed. Releasing the payload is achieved using a 3D printed system based on rack and pinion gears. In addition, auto flight program is developed to enable the autonomous movement of the drone. As a proof-of-concept, a small drone known as "Phantom DJI" is used for .6 kg autonomous payload transport along a predefined route to a target location.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Physical Cyber-Security of SCADA Systems Cluster-Based Hungarian Approach to Task Allocation for Unmanned Aerial Vehicles Privacy Preserving Medium Access Control Protocol for wireless Body Area Sensor Networks Gaussian Beam Propagation Through Turbulent Atmosphere using Second-Order Split-Step Algorithm A generalized equivalent circuit model for large-scale battery packs with cell-to-cell variation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1