GNSS-based navigation systems of autonomous drone for delivering items

Patrik, Aurello; Utama, Gaudi; Gunawan, Alexander Agung Santoso; Chowanda, Andry; Suroso, Jarot S.; Shofiyanti, Rizatus; Budiharto, Widodo

doi:10.1186/s40537-019-0214-3

Cited by 44 publications

(14 citation statements)

References 15 publications

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“…Recently UAVs have been experimented with for delivering items, for instance, the Amazon Prime Air service parcel delivery to customers and delivery of important medical aids for patients in emergency situations [54][55][56]. Findings from a recent study show that the average positional error of landing position between the actual landing spot and the desired landing spot in the UAV delivery experiment was in the order of 1.1 m using the GNSS technology [55]. Obviously, the use of GNSS-RTN technology to support UAV navigation is expected to alleviate the errors in the landing position.…”

Section: Unmanned Aerial Vehicles (Uavs)mentioning

confidence: 99%

The Role of GNSS-RTN in Transportation Applications

et al. 2022

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The Global Navigation Satellite System—Real-Time Network (GNSS-RTN) is a satellite-based positioning system using a network of ground receivers (also called continuously operating reference stations (CORSs)) and a central processing center that provides highly accurate location services to the users in real-time over a broader geographic region. Such systems can provide geospatial location data with centimeter-level accuracy anywhere within the network. Geospatial location services are not only used in measuring ground distances and mapping topography; they have also become vital in many other fields such as aerospace, aviation, natural disaster management, and agriculture, to name but a few. The innovative and multi-disciplinary applications of geospatial data drive technological advancement towards precise and accurate location services available in real-time. Although GNSS-RTN technology is currently utilized in a few industries such as precision farming, construction industry, and land surveying, the implications of precise real-time location services would be far-reaching and more critical to many advanced transportation applications. The GNSS-RTN technology is promising in meeting the needs of automation in most advanced transportation applications. This article presents an overview of the GNSS-RTN technology, its current applications in transportation-related fields, and a perspective on the future use of this technology in advanced transportation applications.

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Section: Unmanned Aerial Vehicles (Uavs)mentioning

confidence: 99%

The Role of GNSS-RTN in Transportation Applications

et al. 2022

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“…Additionally, IoT sensors may be used to monitor the health and well-being of farm animals. References [18,19] proposed a device that is based on the satellite navigation system to track the position of an object to which it is attached. The position is transmitted through an available wireless transmission medium such as a radio frequency, wireless, or cellular network.…”

Section: Related Workmentioning

confidence: 99%

Smart Farming: An Enhanced Pursuit of Sustainable Remote Livestock Tracking and Geofencing Using IoT and GPRS

Ilyas

Ahmad

2020

Wireless Communications and Mobile Computing

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The farmers of agricultural farms manage and monitor different types of livestock. The manual inspection and monitoring of livestock are tedious since the cattle do not stay at fixed locations. Fencing many cattle requires a considerable cost and involves farmers’ physical intervention to keep an eye to stop them from crossing beyond the access points. Visual tracking of livestock and fencing is a time-consuming and challenging job. This research proposes a smart solution for livestock tracking and geofencing using state-of-the-art IoT technology. The study creates a geographical safe zone for cattle based on IoT and GPRS, where the cattle are assigned dedicated IoT sensors. The cattle can be easily remotely monitored and controlled without having any need for farmers to intervene for livestock management physically. The smart system collects the data regarding the location, well-being, and health of the livestock. This kind of livestock management may help prevent the spread of COVID-19, lower the farming costs, and enable remote monitoring.

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“…Various navigation methods have been proposed and they can be mainly divided into three categories: satellite navigation, inertial navigation, and vision-based navigation. UAV navigation using GNSSs is the classical method in which single-frequency receivers are most commonly used [ 19 , 20 ]. A popular and important topic is navigation in an environment where a GNSS is difficult to access or unavailable [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

Analysis of GPS/EGNOS Positioning Quality Using Different Ionospheric Models in UAV Navigation

Grunwald

Ciećko

Kozakiewicz

et al. 2023

Sensors

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Unmanned aerial vehicles (UAVs) have become very popular tools for geoinformation acquisition in recent years. They have also been applied in many other areas of life. Their navigation is highly dependent on global navigation satellite systems (GNSS). The European Geostationary Navigation Overlay Service (EGNOS) is intended to support GNSSs during positioning, mainly for aeronautical applications. The research presented in this paper concerns the analysis of the positioning quality of a modified GPS/EGNOS algorithm. The calculations focus on the source of ionospheric delay data as well as on the aspect of smoothing code observations with phase measurements. The modifications to the algorithm concerned the application of different ionospheric models for position calculation. Consideration was given to the EGNOS ionospheric model, the Klobuchar model applied to the GPS system, the Klobuchar model applied to the BeiDou system, and the NeQuick model applied to the Galileo system. The effect of removing ionospherical corrections from GPS/EGNOS positioning on the results of the determination of positioning quality was also analysed. The results showed that the original EGNOS ionospheric model maintains the best accuracy results and a better correlation between horizontal and vertical results than the other models examined. The additional use of phase-smoothing of code observations resulted in maximum horizontal errors of approximately 1.3 m and vertical errors of approximately 2.2 m. It should be noted that the results obtained have local characteristics related to the area of north-eastern Poland.

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GNSS-based navigation systems of autonomous drone for delivering items

Cited by 44 publications

References 15 publications

The Role of GNSS-RTN in Transportation Applications

The Role of GNSS-RTN in Transportation Applications

Smart Farming: An Enhanced Pursuit of Sustainable Remote Livestock Tracking and Geofencing Using IoT and GPRS

Analysis of GPS/EGNOS Positioning Quality Using Different Ionospheric Models in UAV Navigation

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