2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)最新文献_第4页

RED UAS 2019 Committees RED was 2019委员会

2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS) Pub Date : 2019-11-01 DOI: 10.1109/reduas47371.2019.8999676

引用次数: 0

RED UAS 2019 Keyword Index RED was 2019关键词索引

2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS) Pub Date : 2019-11-01 DOI: 10.1109/reduas47371.2019.8999684

引用次数: 0

An Improved ORB-SLAM2 in Dynamic Scene with Instance Segmentation 基于实例分割的动态场景改进ORB-SLAM2

2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS) Pub Date : 2019-11-01 DOI: 10.1109/REDUAS47371.2019.8999687

Huaming Qian, Pengheng Ding

引用次数: 2

RED UAS 2019 Content List RED was 2019内容列表

2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS) Pub Date : 2019-11-01 DOI: 10.1109/reduas47371.2019.8999716

引用次数: 0

Sensor Fault Mitigation for MAVs under Ground Effect* 地面效应下MAVs传感器故障缓解*

2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS) Pub Date : 2019-11-01 DOI: 10.1109/REDUAS47371.2019.8999709

A. Matus-Vargas, G. Rodríguez-Gómez, J. Martínez-Carranza

引用次数: 1

Observability-Enhancement Optimal Guidance Law 可观察性增强最优制导律

2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS) Pub Date : 2019-11-01 DOI: 10.1109/REDUAS47371.2019.8999706

Shaoming He, Hyo-Sang Shin, W. Ra, A. Tsourdos

引用次数: 1

Development of a Neural Network-based Adaptive Nonlinear Dynamic Inversion Controller for a Tilt-wing VTOL Aircraft 为倾斜翼 VTOL 飞机开发基于神经网络的自适应非线性动态反转控制器

2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS) Pub Date : 2019-11-01 DOI: 10.1109/REDUAS47371.2019.8999700

Johannes Autenrieb, Hyo-Sang Shin, M. Bacic

{"title":"Development of a Neural Network-based Adaptive Nonlinear Dynamic Inversion Controller for a Tilt-wing VTOL Aircraft","authors":"Johannes Autenrieb, Hyo-Sang Shin, M. Bacic","doi":"10.1109/REDUAS47371.2019.8999700","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999700","url":null,"abstract":"This paper presents an adaptive control strategy for a tilt-wing vertical take-off and landing (VTOL) aircraft system. To solve the highly nonlinear control problem, a time-scale separated nonlinear dynamic inversion (NDI) control scheme is proposed to regulate a VTOL aircraft system. In order to handle the existing model uncertainties, an adaptive neural network (ANN) is additionally introduced to the flight control strategy. Due to the fact that the tilt-wing aircraft is able to operate in a conventional take-off and landing (CTOL) mode as well as in a multi-copter VTOL mode, two distinct flight control systems for each mode have been implemented. In order to ensure a safe transition between both modes, a tilt angle-depending linear control mixing approach is applied. The performance of the suggested control approach is investigated by utilising a high fidelity nonlinear flight dynamics model of the tilt-wing system. The results presented demonstrate that the proposed approach provides significant benefits for the robust control of the tilt-wing system.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126773125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Aerial Geo-Localisation for MAVs using PoseNet 利用PoseNet进行无人机空中地理定位

2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS) Pub Date : 2019-11-01 DOI: 10.1109/REDUAS47371.2019.8999713

A. Cabrera-Ponce, J. Martínez-Carranza

{"title":"Aerial Geo-Localisation for MAVs using PoseNet","authors":"A. Cabrera-Ponce, J. Martínez-Carranza","doi":"10.1109/REDUAS47371.2019.8999713","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999713","url":null,"abstract":"The Global Position System (GPS) has become an essential sensor for drones. Autonomous flight in outdoor areas is possible thanks to the use of GPS that enables the drone to obtain its position in latitude and longitude coordinates. However, GPS may become unreliable when the drone flies in environments where the signal may get occluded. Malicious attacks may also compromise the GPS signal, aiming at blocking the signal or replacing it with spurious data. Motivated by these scenarios, we present preliminary results of a methodology aimed at estimating the GPS position of a drone using Convolutional Neural Networks (CNN) and a learning-based strategy. For the latter, we have adopted the PoseNet CNN architecture, originally proposed to address the relocalisation or kidnapping camera problem for facing forward cameras. First we trained PoseNet with a set of aerial images captured with an on-board camera, providing X, Y and Z coordinates as labels, which are obtained from converting GPS coordinates into metres for X and Y, and using the altimeter for Z. Then we perform validation flights where the vehicle follows a different trajectory to that used for collecting the training datasets. Even when the terrain includes bushes and repetitive texture, the CNN returns predictions with an error around the 2.5 metres and a processing speed of 15 milliseconds on average. We argue that a system such as this could be used as an emergency option to return the drone to home in the event of GPS failure. To our knowledge, this is the first time PoseNet is tested to address the problem of geo-localisation of aerial images.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126941184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Robonomics as a Blockchain-based Platform for Unmanned Traffic Management of Mobile Vehicles 基于区块链的移动车辆无人交通管理平台Robonomics

2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS) Pub Date : 2019-11-01 DOI: 10.1109/REDUAS47371.2019.8999696

A. Kapitonov, Ivan Berman, Vadim Manaenko, Vyacheslav Rzhevskiy, Vitaly Bulatov, A. Zenkin

{"title":"Robonomics as a Blockchain-based Platform for Unmanned Traffic Management of Mobile Vehicles","authors":"A. Kapitonov, Ivan Berman, Vadim Manaenko, Vyacheslav Rzhevskiy, Vitaly Bulatov, A. Zenkin","doi":"10.1109/REDUAS47371.2019.8999696","DOIUrl":"https://doi.org/10.1109/REDUAS47371.2019.8999696","url":null,"abstract":"The article describes the concept of a decentralized architecture of a traffic management system for mobile vehicles and is a continuation of the results presented in the previous article “Blockchain-based protocol of autonomous business activity for multi-agent systems consisting of UAVs.. Robonomic protocol is the basis for the system architecture — a combination of the decentralized Ethereum computer, the IPFS distributed file system, Robot Operating System and market mechanisms. In particular, its focused on the principle of communication between nodes of the traffic management system and the stages of the unmanned mission. As a proof of concept, two experiments on the integration of the proposed architecture are presented: air quality measurements using unmanned aerial systems (UAS) and water quality measurements using unmanned surface vessels (USV). Our work demonstrates that distributed ledger and smart contracts technologies are applicable to the traffic management system and increases the transparency and immutability of the data.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130646316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

RED UAS 2019 Book of Abstracts RED UAS 2019摘要书

2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS) Pub Date : 2019-11-01 DOI: 10.1109/reduas47371.2019.8999682

引用次数: 0