scholarly journals Cooperated Routing Problem for Ground Vehicle and Unmanned Aerial Vehicle: The Application on Intelligence, Surveillance and Reconnaissance Missions

2019 ◽  
Author(s):  
Yao Liu ◽  
Zhihao Luo ◽  
Zhong Liu ◽  
Jianmai Shi ◽  
Guangquan Cheng
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Base Station ◽  
Mixed Integer ◽  
Routing Problem ◽  
Ground Vehicle ◽  
Mip Model ◽  
Aerial Vehicle ◽  
Set Up ◽  
Operational Constraints ◽  
Mobile Base

In this paper, we present a novel Two-Echelon Ground Vehicle and Its Mounted Unmanned Aerial Vehicle Cooperated Routing Problem (2E-GUCRP). The 2E-GUCRP arises in the field of Unmanned Aerial Vehicle (UAV) Routing Problem such as those encountered in the context of city logistics. In a typical cooperated system, the UAV is launched from the Ground Vehicle (GV) and automatically flies to the designated target. Meanwhile, acting as a mobile base station, the GV can charge or change the UAV’s battery on the designated landing points to enable the UAV to continue its mission. The objective is to design efficient GV and UAV routes to minimize the total mission time while meeting the operational constraints. A Mixed Integer Programming (MIP) model, which could be solved by commercial software, is constructed to describe this problem. In order to quickly solve the medium-scale problems, two existing heuristics to solve 2E-VRP are improved. The computational experiments are set up to compare our model with the 2E-VRP. The results indicate that the 2E-GUCRP obtains a better efficiency. Further discussion of the practical instance points out that the increase in efficiency is related to the speed relationship between the GV and the UAV.

scholarly journals Impact of UAV Delivery on Sustainability and Costs under Traffic Restrictions

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yuyu Li ◽  
Wei Yang ◽  
Bo Huang
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Unmanned Aerial Vehicle ◽  
Environmental Sustainability ◽  
Mixed Integer ◽  
Environmental Aspects ◽  
Routing Problem ◽  
Vehicle Type ◽  
Aerial Vehicle ◽  
Reduce Energy Consumption

Compared with traditional vehicles delivery, unmanned aerial vehicle (UAV) delivery can reduce energy consumption and greenhouse gas emissions, which benefits environmental sustainability. Besides, UAVs can overcome traffic restrictions, which are the big obstacle in parcel delivery. In reality, there are two kinds of most popular traffic restrictions, vehicle-type restriction, and half-side traffic. We propose a mixed-integer (0-1 linear) green routing model with these two kinds of traffic restrictions for UAVs to exploit the environmental aspects of the use of UAVs in logistics. A genetic algorithm is proposed to efficiently solve the complex routing problem, and an experimental analysis is made to illustrate and validate our model and the algorithm. We found that, under both these two traffic restrictions, UAV delivery can accomplish deliveries that cannot be carried out or are carried out at much higher costs by vehicles only and can always effectively save costs and cut CO2 emissions, which is environmentally friendly. Furthermore, UAV delivery saves more cost and cuts more CO2 emission under the first kind of traffic restriction than that under the second.

Fair Deployment of an Unmanned Aerial Vehicle Base Station for Maximal Coverage

2019 ◽  
Vol E102.B (10) ◽  
pp. 2014-2020
Author(s):  
Yancheng CHEN ◽  
Ning LI ◽  
Xijian ZHONG ◽  
Yan GUO
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Base Station ◽  
Aerial Vehicle

scholarly journals Post-Disaster Unmanned Aerial Vehicle Base Station Deployment Method Based on Artificial Bee Colony Algorithm

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 168327-168336 ◽  
Author(s):  
Jialiuyuan Li ◽  
Dianjie Lu ◽  
Guijuan Zhang ◽  
Jie Tian ◽  
Yawei Pang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Base Station ◽  
Bee Colony ◽  
Aerial Vehicle ◽  
Post Disaster

Investigation of wind and sound field characteristics of multi-rotor unmanned aerial vehicle

2020 ◽  
Vol 51 (7-9) ◽  
pp. 158-163
Author(s):  
Huiru Cao ◽  
Haixiu Cheng ◽  
Wenjian Zhu
Keyword(s):  
Linear Relationship ◽  
Unmanned Aerial Vehicle ◽  
Wind Field ◽  
Sound Field ◽  
Sound Intensity ◽  
Experimental Platform ◽  
Distance Range ◽  
Aerial Vehicle ◽  
Set Up ◽  
Wind Intensity

Wind field and sound field characteristics are the key indexes for unmanned aerial vehicle. Therefore, in this study, the wind field and sound field characteristics of a quad-rotor unmanned aerial vehicle are investigated. First, the experimental platform was set up based on quad-rotor unmanned aerial vehicle. Second, the experiments were performed on the wind field and the sound field characteristics of the unmanned aerial vehicle at different working currents. Then, the experiment results were analysed. Meanwhile, the experimental results showed that the working current has a large impact on the wind field and the wind intensity increases as working current increases; as the working current increases, the sound field is enhanced and a linear relationship exists; within a certain distance range of the unmanned aerial vehicle, as distance increases, sound intensity dramatically decreases. The presented methods and results can not only be used to evaluate the performance of the electric multi-rotor unmanned aerial vehicle but also provide references for the further improvement of the performance of the unmanned aerial vehicle.

scholarly journals Editorial for the Special Issue “Estimation of Crop Phenotyping Traits using Unmanned Ground Vehicle and Unmanned Aerial Vehicle Imagery”

2020 ◽  
Vol 12 (6) ◽  
pp. 940 ◽  
Author(s):  
Xiuliang Jin ◽  
Zhenhai Li ◽  
Clement Atzberger
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Crop Production ◽  
Unmanned Ground Vehicle ◽  
Special Issue ◽  
Climate Conditions ◽  
Ground Vehicle ◽  
Global Food Security ◽  
3D Data ◽  
Potential Applications ◽  
Aerial Vehicle

High-throughput crop phenotyping is harnessing the potential of genomic resources for the genetic improvement of crop production under changing climate conditions. As global food security is not yet assured, crop phenotyping has received increased attention during the past decade. This spectral issue (SI) collects 30 papers reporting research on estimation of crop phenotyping traits using unmanned ground vehicle (UGV) and unmanned aerial vehicle (UAV) imagery. Such platforms were previously not widely available. The special issue includes papers presenting recent advances in the field, with 22 UAV-based papers and 12 UGV-based articles. The special issue covers 16 RGB sensor papers, 11 papers on multi-spectral imagery, and further 4 papers on hyperspectral and 3D data acquisition systems. A total of 13 plants’ phenotyping traits, including morphological, structural, and biochemical traits are covered. Twenty different data processing and machine learning methods are presented. In this way, the special issue provides a good overview regarding potential applications of the platforms and sensors, to timely provide crop phenotyping traits in a cost-efficient and objective manner. With the fast development of sensors technology and image processing algorithms, we expect that the estimation of crop phenotyping traits supporting crop breeding scientists will gain even more attention in the future.

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