Global Thresholding for Scene Understanding Towards Autonomous Drone Navigation

2019 ◽  
Vol 23 (5) ◽  
pp. 909-919
Author(s):  
Alvin Wai Chung Lee ◽  
◽  
Suet-Peng Yong ◽  
Junzo Watada
Keyword(s):  
Object Detection ◽  
Unmanned Aerial Vehicles ◽  
Autonomous Navigation ◽  
Processing Time ◽  
Scene Understanding ◽  
Regions Of Interest ◽  
Gaussian Filter ◽  
Aerial Vehicles ◽  
Global Thresholding

Unmanned aerial vehicles, more typically known as drones are flying aircrafts that do not have a pilot onboard. For drones to fly through an area without GPS signals, developing scene understanding algorithms to assist in autonomous navigation will be useful. In this paper, various thresholding algorithms are evaluated to enhance scene understanding in addition to object detection. Based on the results obtained, Gaussian filter global thresholding can segment regions of interest in the scene effectively and provide the least cost of processing time.

Image matching applied to autonomous navigation of unmanned aerial vehicles

2016 ◽  
Vol 6 (4) ◽  
pp. 205 ◽  
Author(s):  
C.A.O. Silva ◽  
G.A.M. Goltz ◽  
E.H. Shiguemori ◽  
C.L. De Castro ◽  
H.F. De C. Velho ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Image Matching ◽  
Autonomous Navigation ◽  
Aerial Vehicles

scholarly journals Development of Radio-Frequency Sensor Wake-Up with Unmanned Aerial Vehicles as an Aerial Gateway

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1047 ◽  
Author(s):  
Jianfei Chen ◽  
Zhaohua Dai ◽  
ZhiQiang Chen
Keyword(s):  
Energy Efficiency ◽  
Radio Frequency ◽  
Unmanned Aerial Vehicles ◽  
Autonomous Navigation ◽  
Engineering Practice ◽  
Opportunistic Sensing ◽  
Aerial Vehicles ◽  
Frequency Sensor ◽  
Sensing Platform ◽  
Radio Frequency Sensor

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.

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