scholarly journals Motion Estimation by Hybrid Optical Flow Technology for UAV Landing in an Unvisited Area

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1380 ◽  
Author(s):  
Hsiu-Wen Cheng ◽  
Tsung-Lin Chen ◽  
Chung-Hao Tien
Keyword(s):  
Motion Estimation ◽  
Optical Flow ◽  
Global Positioning System ◽  
Prior Information ◽  
Accurate Result ◽  
Multi Scale ◽  
Hybrid Framework ◽  
Global Positioning ◽  
Aerial Vehicle ◽  
The Common

The capability of landing on previously unvisited areas is a fundamental challenge for an unmanned aerial vehicle (UAV). In this paper, we developed a vision-based motion estimation as an aid to improve landing performance. As an alternative to the common scenarios accompanying by external infrastructures or well-defined marker, the proposed hybrid framework can successfully land on a new area without any prior information about guiding marks. The implementation was based on the optical flow technique associated with a multi-scale strategy to overcome the decreasing field-of-view during the UAV descending. Compared with a commercial Global Positioning System (GPS) through a sequence of flight trials, the vision-aided scheme can effectively minimize the possible sensing error, thus, leading to a more accurate result. Moreover, this work has potential to integrate the fast-growing image learning process and yields more practical versatility for UAV applications in the future.

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.

UAV and the comparison of image processing software

2017 ◽  
Vol 5 (1) ◽  
pp. 18-27 ◽  
Author(s):  
Dimitris Kaimaris ◽  
Petros Patias ◽  
Maria Sifnaiou
Keyword(s):  
Image Processing ◽  
Global Positioning System ◽  
Design Methodology ◽  
Surface Model ◽  
Content Type ◽  
Global Positioning ◽  
Erdas Imagine ◽  
Aerial Vehicle ◽  
Processing Software ◽  
Image Processing Software

Purpose The purpose of this paper is to discuss unmanned aerial vehicle (UAV) and the comparison of image processing software. Design/methodology/approach Images from a drone are used and processed with new digital image processing software, Imagine UAV® of Erdas imagine 2015®. The products (Digital Surface Model and ortho images) are validated with check points (CPs) measured in the field with Global Positioning System. Moreover, similar products are produced by Agisoft PhotoScan® software and are compared with both the products of Imagine UAV and the CPs. Findings The results reveal that the two software tools are almost equivalent, while the accuracies of their products are similar to the accuracies of the external orientations of drone images. Originality/value Comparison of image processing software.

scholarly journals PERANCANGAN ALAT PENGGERAK ANTENA MENGGUNAKAN METODE KONTROL PROPORTIONAL, INTEGRAL, DERIVATIVE (PID) UNTUK MELACAK OBJEK BERGERAK

Transmisi ◽  
2018 ◽  
Vol 20 (2) ◽  
pp. 71
Author(s):  
Bagus Bernadi Saputra ◽  
Wahyudi Wahyudi ◽  
Sudjadi Sudjadi
Keyword(s):  
Global Positioning System ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Base Station ◽  
Ground Control ◽  
Positioning System ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Global Positioning ◽  
Aerial Vehicle

Base station atau Ground Control Station (GCS) umumnya menggunakan antena directional untuk dapat berkomunikasi dengan objek bergerak seperti roket dan Unmanned Aerial Vehicle (UAV). Antena directional memiliki jarak jangkau yang jauh, namun memiliki sudut pancar yang sempit. Untuk mengatasi kekurangan dari antena directional, diperlukan alat yang dapat menggerakkan antena ke arah objek bergerak secara nyata pada kisaran sudut azimut dan elevasi. Pada penelitian ini, dirancang alat penggerak antena menggunakan metode kontrol Proportional, Integral, dan Derivative (PID) untuk melacak objek bergerak berbasis Global Positioning System (GPS) dan sensor barometer. Dari hasil perancangan dengan menggunakan nilai parameter PID yang digunakan pada sudut elevasi (Kp=0,03, Ti=150, dan Td=0,22) menghasilkan plant yang mampu mencapai setpoint (74o) dalam waktu 2 detik. Parameter PID yang digunakan pada sudut azimut (Kp=3,5, Ti=100, dan Td=0,09) menghasilkan plant yang mampu mencapai setpoint (180o) dalam waktu 1,1 detik. Dari hasil pengujian, diketahui antena dapat mengikuti objek bergerak (drone) dengan waktu terlama 1 detik pada plant azimut dan 1,5 detik pada plant elevasi. Plant elevasi memiliki Mean Absolute Error (MAE) = 6,54o dan plant azimut memiliki MAE = 8,04o.

Optical Flow-Based Monocular Vision/INS Integrated Navigation for Mobile Robot Indoors

2014 ◽  
Vol 538 ◽  
pp. 375-378 ◽  
Author(s):  
Xi Yuan Chen ◽  
Jing Peng Gao ◽  
Yuan Xu ◽  
Qing Hua Li
Keyword(s):  
Mobile Robot ◽  
Optical Flow ◽  
Global Positioning System ◽  
Autonomous Navigation ◽  
Image Sequences ◽  
Velocity Estimation ◽  
Monocular Vision ◽  
Integrated Navigation ◽  
Global Positioning ◽  
Flow Algorithm

This paper proposed a new algorithm for optical flow-based monocular vision (MV)/ inertial navigation system (INS) integrated navigation. In this mode, a downward-looking camera is used to get the image sequences, which is used to estimate the velocity of the mobile robot by using optical flow algorithm. INS is employed for the yaw variation. In order to evaluate the performance of the proposed method, a real indoor test has done. The result shows that the proposed method has good performance for velocity estimation. It can be applied to the autonomous navigation of mobile robots when the Global Positioning System (GPS) and code wheel is unavailable.

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.

scholarly journals Comparison of L1 and L5 Bands GNSS Signals Acquisition

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2779 ◽  
Author(s):  
Jérôme Leclère ◽  
René Landry Jr. ◽  
Cyril Botteron
Keyword(s):  
Global Positioning System ◽  
Satellite System ◽  
Positioning System ◽  
Global Positioning ◽  
Accurate Comparison ◽  
The Common ◽  
Parallel Code ◽  
L5 Signal ◽  
Global Navigation Satellite ◽  
Pilot Channel

Nowadays, civil Global Navigation Satellite System (GNSS) signals are available in both L1 and L5 bands. A receiver does not need to acquire independently the signals in both bands coming from a same satellite, since their carrier Doppler and code delay are closely related. Therefore, the question of which one to acquire first rises naturally. Although the common thought would tell the L1 band signals which are narrowband, an accurate comparison has never been done, and the decision is not as easy as it seems. Indeed, L5 band signals have several advantages such as stronger power, lower carrier Doppler, or a pilot channel, unlike the Global Positioning System (GPS) L1 C/A signal. The goal of this paper is therefore to compare the acquisition of L1 and L5 bands signals (GPS L1 C/A and L5, Galileo E1 and E5a/b) to determine which one is more complex and by which factor, in terms of processing time and memory, considering hardware receivers and the parallel code search. The results show that overall the L5 band signals are more complex to acquire, but it depends strongly on the conditions. The E5 signal is always more complex to acquire than E1, while the L5 signal can have a complexity close to the L1 C/A in some cases. Moreover, precise assistance providing accurate Doppler could significantly reduce the L5 complexity below the L1 complexity.

A Dual-IMU/GPS based Geolocation System

2011 ◽  
Vol 65 (1) ◽  
pp. 113-123 ◽  
Author(s):  
Jong Ki Lee ◽  
Christopher Jekeli
Keyword(s):  
Kalman Filter ◽  
Global Positioning System ◽  
Unscented Kalman Filter ◽  
Unexploded Ordnance ◽  
Gps Receiver ◽  
Detection Systems ◽  
Kalman Smoother ◽  
Global Positioning ◽  
Measurement Units ◽  
The Common

To improve the geolocation performance of an Unexploded Ordnance (UXO) survey platform, a geodetic Global Positioning System (GPS) receiver was combined with two tactical-grade Inertial Measurement Units (IMUs) and mounted on two types of detection systems. Analysis of data collected for typical trajectories focused on the dual-IMU/GPS pre/post processing using optimal nonlinear estimation together with a Wave Correlation Filter (WCF) and end-matching. Each trajectory of the platforms was estimated by the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). The WCF was then applied to the two solutions of the platform trajectories derived from each IMU in order to extract the common components in the frequency domain, assuming that uncorrelated components are errors. The remaining bias and trends of the estimated position results were further removed by end-matching IMU solutions and GPS update points. The results of these methods were applied to our field test data to show that the WCF and end-matching can improve position accuracy from 4% to 14% with respect to the Unscented Kalman Smoother (UKS) solution alone.

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