Cooperative Navigation between a Ground Vehicle and an Unmanned Aerial Vehicle in GNSS-Challenged Environments

2016 ◽  
Author(s):  
Victor O. Sivaneri ◽  
Jason N. Gross
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Ground Vehicle ◽  
Cooperative Navigation ◽  
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.

scholarly journals Robotic complex for inspection of the outer surface of the aircraft in its parking lot

2020 ◽  
Vol 12 (S) ◽  
pp. 21-31
Author(s):  
Boris S. ALESHIN ◽  
Alexander I. CHERNOMORSKY ◽  
Eduard D. KURIS ◽  
Konstantin S. LELKOV ◽  
Maxim V. IVAKIN
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Outer Surface ◽  
Unmanned Ground Vehicle ◽  
Metal Fatigue ◽  
Ground Vehicle ◽  
Extreme Wind ◽  
Parking Lot ◽  
Wind Exposure ◽  
Wind Actions ◽  
Aerial Vehicle

Through-flight inspection of the outer surface of the aircraft is necessary to identify possible damage to the surface of the aircraft caused by metal fatigue, lightning, birds collision, etc. The article discusses the method of robotic inspection of the outer surface of the aircraft in its open air parking area. The robotic complex (RC) consists of an unmanned ground vehicle (UGV) and an unmanned aerial vehicle (UAV) interconnected by a tether mechanism (TM). The algorithm of the RC functioning is presented. The main attention is paid to the formation of the TM control and the features of its work, ensuring the prevention of collisions of UAV with aircraft during extreme wind actions on UAV. The study of the most critical mode of the complex operation under extreme wind actions on an unmanned aerial vehicle is carried out. The results of modeling the typical process of the RC operation in an abnormal conditions of extreme wind exposure to UAV are presented.

An Intelligent Ground-Air Cooperative Navigation Framework Basedon Visual-Aided Method in Indoor Environments

2021 ◽  
pp. 1-10
Author(s):  
Zi-Hao Wang ◽  
Kai-Yu Qin ◽  
Te Zhang ◽  
Bo Zhu
Keyword(s):  
Navigation System ◽  
Reconstruction Method ◽  
Indoor Environments ◽  
Ground Vehicle ◽  
Cooperative Navigation ◽  
Localization And Mapping ◽  
Small Uav ◽  
Actual Environment ◽  
Heterogeneous Robots ◽  
Aerial Vehicle

In the future, heterogeneous robots are expected to perform more complex tasks in a cooperative manner, and the onboard navigation system is required to be capable of working safely and effectively in the area where GNSS signal is weak or even could not be received. To demonstrate this concept, we have developed a cooperative navigation system by the use of Ground-Aerial Vehicle Cooperation. The key innovations of the development lie in the following aspects: (1) a local scalable self-organizing network is constructed for data interaction between a small UAV and a reusable ground robot; (2) a new navigation framework is proposed to achieve visual simultaneous localization and mapping (SLAM) where carrying capacity of both the ground vehicle and UAV are systematically considered; (3) an octomap-based 3D environment reconstruction method is developed to achieve map pre-establishment in complex navigation environments, and the classic ORB-SLAM2 system is improved to be adaptive to actual environment exploration and perception. In-door flight experiments demonstrate the effectiveness of the proposed solution. More interestingly, by implementing a centroid tracking algorithm, the cooperative system is further capable of tracking a man moving in indoor environments.

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