Unmanned Aerial Vehicle Photogrammetric Results Using Different Real Time Kinematic Global Positioning System Approaches

2013 ◽  
pp. 123-134 ◽  
Author(s):  
Khairul Nizam Tahar ◽  
Anuar Ahmad ◽  
Wan Abdul Aziz Wan Mohd Akib ◽  
Wan Mohd Naim Wan Mohd
Keyword(s):  
Real Time ◽  
Unmanned Aerial Vehicle ◽  
Global Positioning System ◽  
Positioning System ◽  
Real Time Kinematic ◽  
Global Positioning ◽  
Aerial Vehicle ◽  
System Approaches

scholarly journals A low-cost solution for unmanned aerial vehicle navigation in a global positioning system–denied environment

2018 ◽  
Vol 14 (6) ◽  
pp. 155014771878175 ◽  
Author(s):  
Shahrukh Ashraf ◽  
Priyanka Aggarwal ◽  
Praveen Damacharla ◽  
Hong Wang ◽  
Ahmad Y Javaid ◽  
...  
Keyword(s):  
Optical Flow ◽  
Unmanned Aerial Vehicle ◽  
Global Positioning System ◽  
Motion Vector ◽  
Block Matching ◽  
Positioning System ◽  
Simulation Studies ◽  
Flow Measurements ◽  
Global Positioning ◽  
Aerial Vehicle

The ability of an autonomous unmanned aerial vehicle to navigate and fly precisely determines its utility and performance. The current navigation systems are highly dependent on the global positioning system and are prone to error because of global positioning system signal outages. However, advancements in onboard processing have enabled inertial navigation algorithms to perform well during short global positioning system outages. In this article, we propose an intelligent optical flow–based algorithm combined with Kalman filters to provide the navigation capability during global positioning system outages and global positioning system–denied environments. Traditional optical flow measurement uses block matching for motion vector calculation that makes the measurement task computationally expensive and slow. We propose the application of an artificial bee colony–based block matching technique for faster optical flow measurements. To effectively fuse optical flow data with inertial sensors output, we employ a modified form of extended Kalman filter. The modifications make the filter less noisy by utilizing the redundancy of sensors. We have achieved an accuracy of ~95% for all non-global positioning system navigation during our simulation studies. Our real-world experiments are in agreement with the simulation studies when effects of wind are taken into consideration.

scholarly journals Penentuan Lintasan Pergerakan Quadcopter Berbasis GPS (Global Positioning System)

2019 ◽  
Vol 1 (2) ◽  
pp. 1-14
Author(s):  
Abdur Rohman Harits Martawireja ◽  
Hadi Supriyanto
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Global Positioning System ◽  
Positioning System ◽  
Global Positioning ◽  
Aerial Vehicle ◽  
Rotary Wing

UNMANNED AERIAL VEHICLE (UAV) merupakan sebuah kendaraan udara tanpa awak yang dapat dikendalikan. Terdapat dua tipe UAV, yakni fixed wing dan rotary wing. Quadcopter menjadi salah satu tipe UAV rotary wing yang banyak digunakan dalam berbagai kebutuhan, seperti eksplorasi dan pengambilan citra. Pada penelitian ini Quadcopter berfungsi sebagai kendaraan yang harus bergerak mengikuti lintasan, dimana lintasan yang dikuti oleh Quadcopter berasal dari GPS yang dihasilkan oleh objek yang diikuti (Modul Utama). Tipe GPS yang terpasang pada Quadcopter (GPS1) maupun pada Modul Utama (GPS2) adalah  GPS Ublox NEO. Prinsip kerja sistem adalah quadcopter mengikuti Koordinat-koordinat lintasan yang dihasilkan oleh GPS1, di mana data-data lintasan GPS1 dikirim ke Quadcopter menggunakan media Bluetooth.  Dalam pergerakannya, Quadcopter akan terus-menerus membandingkan data-data koordinat yang dihasikan posisi Quadcopter dengan data-data koordinat lintasan yang sudah diterima. Pengujian pada Receiver GPS Modul Utama (GPS1) dan Receiver GPS Quadcoter (GPS2), kedua GPS mampu mendapatkan data GPS dari satelit.  Kesalahan/perbedaan data dari GPS1 dan GPS2  pada pengujian pergerakkan Quadcopter  untuk mengikuti  Modul Utama sebagai titik tujuan sebesar 53% pada garis lintang dan 51% pada garis bujur.

Application of the Real-Time Kinematic Global Positioning System in Bridge Safety Monitoring

2005 ◽  
Vol 10 (2) ◽  
pp. 163-168 ◽  
Author(s):  
Jinjun Guo ◽  
Liang Xu ◽  
Lianjun Dai ◽  
Mike McDonald ◽  
Jianping Wu ◽  
...  
Keyword(s):  
Real Time ◽  
Global Positioning System ◽  
Safety Monitoring ◽  
Positioning System ◽  
The Real ◽  
Bridge Safety ◽  
Real Time Kinematic ◽  
Global Positioning

scholarly journals Camera Assisted Autonomous UAV Landing

2020 ◽  
pp. paper82-1-paper82-10
Author(s):  
Mainak Mondal ◽  
Stanislav Shidlovskiy ◽  
Dmitriy Shashev
Keyword(s):  
Wind Speed ◽  
Unmanned Aerial Vehicle ◽  
Global Positioning System ◽  
Visual Cues ◽  
Experimental Methods ◽  
Research Articles ◽  
Positioning System ◽  
Related Research ◽  
Global Positioning ◽  
Aerial Vehicle

This article describes the use of a monocular camera attached to a multirotor perpendicular to the horizon, to recognize visual cues or artefacts (AprilTag) and use it as an anchor for aerial alignment to finally land on it, thus attempting to make autonomous flights safer and usable in slightly hard-to-reach locations. A Hexacopter frame with the DJI N3 flight controller was used for prototyping and realizing the desired algorithm. Factors like wind speed and gusts were taken into account as well as the center of gravity of the multirotor and the position of the molecular camera attached to the copter facing downwards or at a 90-degree angle. The results of the experiments conducted were verified against existing methods like the GPS (Global Positioning System) waypoint mission provided by major commercial Unmanned Aerial Vehicle(UAV) or Flight Controller manufacturers and were also compared to experimental methods presented in related research articles, fairing excellent results

Sign in / Sign up

Export Citation Format

Share Document