The positioning system use for autonomous navigation of unmanned aerial vehicles

Author(s):  
Qi Zhang ◽  
Yaoxing Wei ◽  
Xiao Li ◽  
Han Xu
2021 ◽  
Vol 3 (1) ◽  
pp. 1-8
Author(s):  
Pawan Thapa

In few years, agriculture drones emerge for monitoring, planting, spraying, and mapping to increase crop production and reduce labor. This review results show its significance and farmer's demand for agriculture. The UAV technologies enable farmer management based on measuring and observation based on real-time crop and livestock monitoring, significantly maximize their production. The farm drone consists of user-friendly software with interactive maps, and a global positioning system will improve production. It will support farmer for farming in efficient, effective, and economical ways.


Author(s):  
C.A.O. Silva ◽  
G.A.M. Goltz ◽  
E.H. Shiguemori ◽  
C.L. De Castro ◽  
H.F. De C. Velho ◽  
...  

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1047 ◽  
Author(s):  
Jianfei Chen ◽  
Zhaohua Dai ◽  
ZhiQiang Chen

The advent of autonomous navigation, positioning, and general robotics technologies has enabled the improvement of small to miniature-sized unmanned aerial vehicles (UAVs, or ‘drones’) and their wide uses in engineering practice. Recent research endeavors further envision a systematic integration of aerial drones and traditional contact-based or ground-based sensors, leading to an aerial–ground wireless sensor network (AG-WSN), in which the UAV serves as both a gateway besides and a remote sensing platform. This paper serves two goals. First, we will review the recent development in architecture, design, and algorithms related to UAVs as a gateway and particularly illustrate its nature in realizing an opportunistic sensing network. Second, recognizing the opportunistic sensing need, we further aim to focus on achieving energy efficiency through developing an active radio frequency (RF)-based wake-up mechanism for aerial–ground data transmission. To prove the effectiveness of energy efficiency, several sensor wake-up solutions are physically implemented and evaluated. The results show that the RF-based wake-up mechanism can potentially save more than 98.4% of the energy that the traditional duty-cycle method would otherwise consume, and 96.8% if an infrared-receiver method is used.


Author(s):  
Dongjin Lee ◽  
Youngjoo Kim ◽  
Hyochoong Bang

A vision-aided terrain referenced navigation (VATRN) approach is addressed for autonomous navigation of unmanned aerial vehicles (UAVs) under GPS-denied conditions. A typical terrain referenced navigation (TRN) algorithm blends inertial navigation data with measured terrain information to estimate vehicle’s position. In this paper, a low-cost inertial navigation system (INS) for UAVs is supplemented with a monocular vision-aided navigation system and terrain height measurements. A point mass filter based on Bayesian estimation is employed as a TRN algorithm. Homograpies are established to estimate the vehicle’s relative translational motion using ground features with simple assumptions. And the error analysis in homography estimation is explored to estimate the error covariance matrix associated with the visual odometry data. The estimated error covariance is delivered to the TRN algorithm for robust estimation. Furthermore, multiple ground features tracked by image observations are utilized as multiple height measurements to improve the performance of the VATRN algorithm.


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