Coevolution Pigeon-Inspired Optimization with Cooperation-Competition Mechanism for Multi-UAV Cooperative Region Search

In this paper, a dynamic two-stage closed search (DTSCS) scheme for the unmanned aerial vehicle (UAV) cooperative region search is designed, which satisfies the range constraint (RC) and orientation constraint (OC). The closed trajectory is composed of two coupling stages, the search stage and the return stage. The position and orientation at the end of the search stage are the starting cell and orientation of the return stage. In the first stage, a coevolution pigeon-inspired optimization (CPIO) algorithm based on the cooperation-competition mechanism is proposed for multi-UAV cooperative search. In the return stage, inspired by region searching and trajectory tracking, a search tracking (ST) approach is presented to obtain the lowest-cost path under OC. The simulation results show that: (i) N p = 5 is the best prediction time step. (ii) CPIO algorithm performs better than the compared intelligent algorithms in region searching. (iii) ST has high tracking performance than other algorithms. (iv) The DTSCS scheme enables every UAV to make the best use of its fuel to cover more region and return to the airport within the RC, and the average range utilization of UAVs is 97% under the 3OC.

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Machine Learning for the Dynamic Positioning of UAVs for Extended Connectivity

Sensors ◽

10.3390/s21134618 ◽

2021 ◽

Vol 21 (13) ◽

pp. 4618

Author(s):

Francisco Oliveira ◽

Miguel Luís ◽

Susana Sargento

Keyword(s):

Machine Learning ◽

Cellular Networks ◽

Real Data ◽

Emerging Technology ◽

Machine Learning Algorithms ◽

Base Stations ◽

Aerial Vehicle ◽

Positioning Algorithm ◽

The Military ◽

Better Than

Unmanned Aerial Vehicle (UAV) networks are an emerging technology, useful not only for the military, but also for public and civil purposes. Their versatility provides advantages in situations where an existing network cannot support all requirements of its users, either because of an exceptionally big number of users, or because of the failure of one or more ground base stations. Networks of UAVs can reinforce these cellular networks where needed, redirecting the traffic to available ground stations. Using machine learning algorithms to predict overloaded traffic areas, we propose a UAV positioning algorithm responsible for determining suitable positions for the UAVs, with the objective of a more balanced redistribution of traffic, to avoid saturated base stations and decrease the number of users without a connection. The tests performed with real data of user connections through base stations show that, in less restrictive network conditions, the algorithm to dynamically place the UAVs performs significantly better than in more restrictive conditions, reducing significantly the number of users without a connection. We also conclude that the accuracy of the prediction is a very important factor, not only in the reduction of users without a connection, but also on the number of UAVs deployed.

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A high-fidelity realization of the Euclid code comparison N-body simulation with Abacus

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/stz634 ◽

2019 ◽

Vol 485 (3) ◽

pp. 3370-3377 ◽

Cited By ~ 8

Author(s):

Lehman H Garrison ◽

Daniel J Eisenstein ◽

Philip A Pinto

Keyword(s):

Power Spectrum ◽

High Performance ◽

High Fidelity ◽

Step Size ◽

Time Step ◽

Code Comparison ◽

Force Accuracy ◽

Integration Errors ◽

Better Than ◽

Good Agreement

Abstract We present a high-fidelity realization of the cosmological N-body simulation from the Schneider et al. code comparison project. The simulation was performed with our AbacusN-body code, which offers high-force accuracy, high performance, and minimal particle integration errors. The simulation consists of 20483 particles in a $500\ h^{-1}\, \mathrm{Mpc}$ box for a particle mass of $1.2\times 10^9\ h^{-1}\, \mathrm{M}_\odot$ with $10\ h^{-1}\, \mathrm{kpc}$ spline softening. Abacus executed 1052 global time-steps to z = 0 in 107 h on one dual-Xeon, dual-GPU node, for a mean rate of 23 million particles per second per step. We find Abacus is in good agreement with Ramses and Pkdgrav3 and less so with Gadget3. We validate our choice of time-step by halving the step size and find sub-percent differences in the power spectrum and 2PCF at nearly all measured scales, with ${\lt }0.3{{\ \rm per\ cent}}$ errors at $k\lt 10\ \mathrm{Mpc}^{-1}\, h$. On large scales, Abacus reproduces linear theory better than 0.01 per cent. Simulation snapshots are available at http://nbody.rc.fas.harvard.edu/public/S2016.

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An orthogonal terrain-following coordinate and its preliminary tests using 2-D idealized advection experiments

Geoscientific Model Development ◽

10.5194/gmd-7-1767-2014 ◽

2014 ◽

Vol 7 (4) ◽

pp. 1767-1778 ◽

Cited By ~ 7

Author(s):

Y. Li ◽

B. Wang ◽

D. Wang ◽

J. Li ◽

L. Dong

Keyword(s):

Rotation Angle ◽

Computational Grids ◽

Time Step ◽

Numerical Errors ◽

Terrain Following ◽

Steep Terrain ◽

Definition Of ◽

Σ Coordinate ◽

Basis Vectors ◽

Better Than

Abstract. We have designed an orthogonal curvilinear terrain-following coordinate (the orthogonal σ coordinate, or the OS coordinate) to reduce the advection errors in the classic σ coordinate. First, we rotate the basis vectors of the z coordinate in a specific way in order to obtain the orthogonal, terrain-following basis vectors of the OS coordinate, and then add a rotation parameter b to each rotation angle to create the smoother vertical levels of the OS coordinate with increasing height. Second, we solve the corresponding definition of each OS coordinate through its basis vectors; and then solve the 3-D coordinate surfaces of the OS coordinate numerically, therefore the computational grids created by the OS coordinate are not exactly orthogonal and its orthogonality is dependent on the accuracy of a numerical method. Third, through choosing a proper b, we can significantly smooth the vertical levels of the OS coordinate over a steep terrain, and, more importantly, we can create the orthogonal, terrain-following computational grids in the vertical through the orthogonal basis vectors of the OS coordinate, which can reduce the advection errors better than the corresponding hybrid σ coordinate. However, the convergence of the grid lines in the OS coordinate over orography restricts the time step and increases the numerical errors. We demonstrate the advantages and the drawbacks of the OS coordinate relative to the hybrid σ coordinate using two sets of 2-D linear advection experiments.

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Exploration of a New Location Algorithm for Wireless Sensor Network

International Journal of Online Engineering (iJOE) ◽

10.3991/ijoe.v14i06.8708 ◽

2018 ◽

Vol 14 (06) ◽

pp. 191

Author(s):

Chao Huang ◽

Yuang Mao

Keyword(s):

Threshold Value ◽

Location Error ◽

Original Algorithm ◽

Node Ratio ◽

Location Algorithm ◽

Beacon Node ◽

New Location ◽

The Average Range ◽

Better Than ◽

Range Calculation

To further study the basic principle and localization process of DV-Hop location algorithm, the location error reason of traditional location algorithm caused by the minimum hop number was analyzed and demonstrated in detail. The RSSI ranging technology was introduced to modify the minimum hops stage, and the minimum hop number was improved by the DV-Hop algorithm. For the location error caused by the average hop distance, the hop distance of the original algorithm was optimized. The improved location algorithm of DV-Hop average hop distance was used to modify the average range calculation by introducing the proportion of beacon nodes and the optimal threshold value. The optimization algorithm of the two different stages was combined into an improved location algorithm based on hop distance optimization, and the advantages of the two algorithms were taken into account.Finally, the traditional DV-Hop location algorithm and the three improved location algorithms were simulated and analyzed by beacon node ratio and node communication radius with multi angle. The experimental results showed that the improved algorithm was better than the original algorithm in the positioning stability and positioning accuracy.

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Multi-UAV Cooperative Task Planning for Border Patrol based on Hierarchical Optimization

Journal of Imaging Science and Technology ◽

10.2352/j.imagingsci.technol.2021.65.4.040402 ◽

2021 ◽

Author(s):

Hai-shi Liu ◽

Yu-xuan Sun ◽

Nan Pan ◽

Qi-yong Chen ◽

Xiao-jue Guo ◽

...

Keyword(s):

Chaos Theory ◽

Hierarchical Optimization ◽

Border Patrol ◽

Complex Environments ◽

Environmental Model ◽

Other Information ◽

Aerial Vehicle ◽

Scene Information ◽

Simulation Results ◽

Multi Uav

In order to improve the patrol efficiency of border patrol drones, based on unmanned aerial vehicle (UAV) border patrol missions in multiple complex environments, this article proposes a whale algorithm based on chaos theory to plan patrol missions for multiple drones. First, according to the terrain the corresponding environmental model is established for the topography and then solved in layers to obtain the number of drones and other information that each base needs to send to the patrol area. Further, the use of drones with cameras and other detection equipment to patrol the scene information and images extract and transfer to the terminal in real time, and further detect suspicious persons and vehicles on the screen. The final simulation results show that the proposed scheme can be effectively applied to the planning of multi-UAV coordinated missions for border patrol.

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Information Distribution in Multi-Robot Systems: Utility-Based Evaluation Model

Sensors ◽

10.3390/s20030710 ◽

2020 ◽

Vol 20 (3) ◽

pp. 710 ◽

Cited By ~ 2

Author(s):

Michał Barciś ◽

Agata Barciś ◽

Hermann Hellwagner

Keyword(s):

Evaluation Model ◽

Proof Of Concept ◽

Information Distribution ◽

Unified Framework ◽

Robot Operating System ◽

Robot Systems ◽

System 2 ◽

Aerial Vehicle ◽

Multi Uav ◽

Multi Robot

This work addresses the problem of information distribution in multi-robot systems, with an emphasis on multi-UAV (unmanned aerial vehicle) applications. We present an analytical model that helps evaluate and compare different information distribution schemes in a robotic mission. It serves as a unified framework to represent the usefulness (utility) of each message exchanged by the robots. It can be used either on its own in order to assess the information distribution efficacy or as a building block of solutions aimed at optimizing information distribution. Moreover, we present multiple examples of instantiating the model for specific missions. They illustrate various approaches to defining the utility of different information types. Finally, we introduce a proof of concept showing the applicability of the model in a robotic system by implementing it in Robot Operating System 2 (ROS 2) and performing a simple simulated mission using a network emulator. We believe the introduced model can serve as a basis for further research on generic solutions for assessing or optimizing information distribution.

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Fractional Vegetation Cover Estimation of Different Vegetation Types in the Qaidam Basin

Sustainability ◽

10.3390/su11030864 ◽

2019 ◽

Vol 11 (3) ◽

pp. 864 ◽

Cited By ~ 6

Author(s):

Siqi Zhang ◽

Hui Chen ◽

Yang Fu ◽

Huihui Niu ◽

Yi Yang ◽

...

Keyword(s):

Vegetation Cover ◽

Arid Regions ◽

Qaidam Basin ◽

High Density ◽

Fractional Vegetation Cover ◽

Steppe Region ◽

New Ideas ◽

Aerial Vehicle ◽

Vegetation Region ◽

Better Than

The estimation of fractional vegetation cover (FVC) by using remote sensing images has become feasible. Based on Landsat8-OLI images and field data obtained from an unmanned aerial vehicle, we established an empirical model (EM) and a pixel decomposition model (PDM) of FVC in the desert vegetation region, steppe vegetation region, meadow vegetation region and mixed vegetation region (the three vegetation region types) of the Qaidam Basin, and the inversion accuracies of the models were compared. The results show the following: (1) Vegetation classification inversion (VCI) provides a promising approach for FVC estimation. The accuracy of FVC by VCI was obviously better than that achieved using vegetation mixed inversion (VMI); (2) Differences were observed in the FVC estimation between VCI and VMI by the EM in areas with relatively high-density vegetation cover (FVC > 60%). The FVC in some parts of steppe region in the basin was slightly overestimated by VMI of the EM; 3) VCI estimated by the PDM resulted in lower inversion values for extremely low-density vegetation cover (FVC ≤ 10%) and higher inversion values for high-density vegetation cover (FVC > 80%). The FVC inversion was underestimated by the PDM in steppe and meadow regions with FVC > 15% in the basin. The application of VCI in different models can provide new ideas for the sustainable study of vegetation in arid regions.

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Multi-UAV Specification and Control with a Single Pilot-in-the-Loop

Unmanned Systems ◽

10.1142/s230138502050020x ◽

2020 ◽

Vol 08 (04) ◽

pp. 269-277

Author(s):

Patricio Moreno ◽

Santiago Esteva ◽

Ignacio Mas ◽

Juan I. Giribet

Keyword(s):

Remote Control ◽

Unmanned Aerial Vehicles ◽

Field Experiments ◽

Aerial Vehicles ◽

Simulated Environment ◽

Aerial Vehicle ◽

Space Formulation ◽

Trajectory Following ◽

And Control ◽

Multi Uav

This work presents a multi-unmanned aerial vehicle formation implementing a trajectory-following controller based on the cluster-space robot coordination method. The controller is augmented with a feed-forward input from a control station operator. This teleoperation input is generated by means of a remote control, as a simple way of modifying the trajectory or taking over control of the formation during flight. The cluster-space formulation presents a simple specification of the system’s motion and, in this work, the operator benefits from this capability to easily evade obstacles by means of controlling the cluster parameters in real time. The proposed augmented controller is tested in a simulated environment first, and then deployed for outdoor field experiments. Results are shown in different scenarios using a cluster of three autonomous unmanned aerial vehicles.

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The Impact of Automation Reliability and Operator Fatigue on Performance and Reliance

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1541931213601047 ◽

2016 ◽

Vol 60 (1) ◽

pp. 211-215 ◽

Cited By ~ 3

Author(s):

Ryan W. Wohleber ◽

Gloria L. Calhoun ◽

Gregory J. Funke ◽

Heath Ruff ◽

C.-Y. Peter Chiu ◽

...

Keyword(s):

Significant Interaction ◽

High Reliability ◽

Task Engagement ◽

Time On Task ◽

Operator Fatigue ◽

Aerial Vehicle ◽

And Performance ◽

Automated Decision Making ◽

The Impact ◽

Multi Uav

Reliability of automation is known to influence operator reliance on automation. What is less understood is how the influence of reliability and the effects of operator fatigue might interact. The present study investigated the impact of automation reliability on accuracy and reliance and how this impact changes with level of fatigue during simulated multiple unmanned aerial vehicle (UAV) operation. Participants ( N = 131) completed a two-hour simulated multi-UAV mission assisted by an automated decision making aid of either high or low reliability. A decrease in subjective task engagement and performance over time marked the induction of passive fatigue by the mission. Participants were more trusting in the high reliability condition than in the low reliability condition. Finally, reliance decreased with time at any reliability, but a significant interaction between reliability and time on task indicated that the decrease was of smaller magnitude when the automation was reliable.

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Generation of High-Resolution Rain Fields in West Africa: Evaluation of Dynamic Interpolation Methods

Journal of Hydrometeorology ◽

10.1175/jhm-d-10-05015.1 ◽

2011 ◽

Vol 12 (6) ◽

pp. 1465-1482 ◽

Cited By ~ 29

Author(s):

T. Vischel ◽

G. Quantin ◽

T. Lebel ◽

J. Viarre ◽

M. Gosset ◽

...

Keyword(s):

High Resolution ◽

West Africa ◽

Evaluation Criteria ◽

Rain Gauge ◽

Time Of Arrival ◽

Time Step ◽

Propagation Models ◽

Interpolation Technique ◽

Classic Approach ◽

Better Than

Abstract High-resolution rain fields are a prerequisite to many hydrometeorological studies. For some applications, the required resolution may be as fine as 1 km in space and 5 min in time. At these scales, rainfall is strongly intermittent, variable in space, and correlated in time because of the propagation of the rainy systems. This paper compares two interpolation approaches to generate high-resolution rain fields from rain gauge measurements: (i) a classic interpolation technique that consists in interpolating independently the rain intensities at each time step (Eulerian kriging) and (ii) a simple dynamic interpolation technique that incorporates the propagation of the rainy systems (Lagrangian kriging). For this latter approach, three propagation models are tested. The different interpolation techniques are evaluated over three climatically contrasted areas in West Africa where a multiyear 5-min rainfall dataset has been collected during the African Monsoon Multidisciplinary Analyses (AMMA) campaigns. The dynamic interpolation technique is shown to perform better than the classic approach for a majority of the rainy events. The performances of the three propagation models differ from one another, depending on the evaluation criteria used. One of them provides a satisfactory time of arrival of rainfall but slightly smooths the rain intensities. The two others reproduce well the rain intensities, but the time of arrival of the rain is sometimes delayed. The choice of an appropriate propagation algorithm will thus depend on the operational objectives underlying the rain field generation.

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