Multi-parametric data recovery for unmanned aerial vehicle navigation system

2016 ◽  
Author(s):  
V.P. Kharchenko ◽  
N.S. Kuzmenko ◽  
A.G. Kukush ◽  
I.V. Ostroumov
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Navigation System ◽  
Data Recovery ◽  
Vehicle Navigation ◽  
Vehicle Navigation System ◽  
Parametric Data ◽  
Aerial Vehicle

scholarly journals Indoor Unmanned Aerial Vehicle Navigation System Using LED Panels and QR Codes

2021 ◽  
Vol 33 (2) ◽  
pp. 242-253
Author(s):  
Hiroyuki Ukida ◽  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Navigation System ◽  
Indoor Environment ◽  
Flight Path ◽  
Qr Code ◽  
Qr Codes ◽  
Vehicle Navigation System ◽  
Aerial Vehicle ◽  
Uav Navigation ◽  
Navigation Method

In this study, we propose an unmanned aerial vehicle (UAV) navigation system using LED panels and QR codes as markers in an indoor environment. An LED panel can display various patterns; hence, we use it as a command presentation device for UAVs, and a QR code can embed various pieces of information, which is used as a sign to estimate the location of the UAV on the way of the flight path. In this paper, we present a navigation method from departure to destination positions in which an obstacle lies between them. In addition, we investigate the effectiveness of our proposed method using an actual UAV.

Study of the route correction system for the on-board navigation system of an unmanned aerial vehicle on the grounds of radar images of the terrain

2020 ◽  
pp. 129-134
Keyword(s):  
Predictive Model ◽  
Unmanned Aerial Vehicle ◽  
Predictive Models ◽  
Navigation System ◽  
Error Compensation ◽  
Compensation Scheme ◽  
Radar Images ◽  
Aerial Vehicle ◽  
System Errors ◽  
Correction System

The system of route correction of an unmanned aerial vehicle (UAV) is considered. For the route correction the on-board radar complex is used. In conditions of active interference, it is impossible to use radar images for the route correction so it is proposed to use the on-board navigation system with algorithmic correction. An error compensation scheme of the navigation system in the output signal using the algorithm for constructing a predictive model of the system errors is applied. The predictive model is building using the genetic algorithm and the method of group accounting of arguments. The quality comparison of the algorithms for constructing predictive models is carried out using mathematical modeling.

Self-localization and positioning vehicle navigation system based on computer vision and PID control

2019 ◽  
Author(s):  
Christian Quintanar-Sotelo ◽  
Ernesto Bernal-Ortega ◽  
Adrian Navarro-Carranza ◽  
Alan J. Romo-Munoz ◽  
Jorge A. de la Cruz Morales ◽  
...  
Keyword(s):  
Computer Vision ◽  
Pid Control ◽  
Navigation System ◽  
Vehicle Navigation ◽  
Vehicle Navigation System

Research on Improvement Road Impedance Function Based on Vehicle Navigation System

2013 ◽  
Vol 659 ◽  
pp. 45-48
Author(s):  
Rui Wang ◽  
Zai Tang Wang
Keyword(s):  
Path Planning ◽  
Navigation System ◽  
Vehicle Navigation ◽  
Impedance Function ◽  
Vehicle Navigation System ◽  
Navigation Path ◽  
Planning Algorithm ◽  
Improved Model ◽  
Path Planning Algorithm ◽  
Impedance Functions

Comparing with some widely used road impedance functions, this paper choose BPR model as base model of improvement, and determine the parameter of BPR model. We apply the improved model to vehicle navigation system in the path planning algorithm, and experiments proved that the model satisfies navigation path planning requirement and have universal performance.

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