scholarly journals Mission Planning for Unmanned Aerial Vehicles Based on Voronoi Diagram-Tabu Genetic Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wei Tan ◽  
Yong-jiang Hu ◽  
Yue-fei Zhao ◽  
Wen-guang Li ◽  
Xiao-meng Zhang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Unmanned Aerial Vehicles ◽  
Voronoi Diagram ◽  
Pso Algorithm ◽  
Mission Planning ◽  
Cooperative System ◽  
Aerial Vehicles ◽  
Rendezvous Problem ◽  
Aerial Vehicle ◽  
Multi Uav

Unmanned aerial vehicles (UAVs) are increasingly used in different military missions. In this paper, we focus on the autonomous mission allocation and planning abilities for the UAV systems. Such abilities enable adaptation to more complex and dynamic mission environments. We first examine the mission planning of a single unmanned aerial vehicle. Based on that, we then investigate the multi-UAV cooperative system under the mission background of cooperative target destruction and show that it is a many-to-one rendezvous problem. A heterogeneous UAV cooperative mission planning model is then proposed where the mission background is generated based on the Voronoi diagram. We then adopt the tabu genetic algorithm (TGA) to obtain multi-UAV mission planning. The simulation results show that the single-UAV and multi-UAV mission planning can be effectively realized by the Voronoi diagram-TGA (V-TGA). It is also shown that the proposed algorithm improves the performance by 3% in comparison with the Voronoi diagram-particle swarm optimization (V-PSO) algorithm.

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

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.

A constraint-based approach for planning unmanned aerial vehicle activities

2016 ◽  
Vol 31 (5) ◽  
pp. 486-497
Author(s):  
Christophe Guettier ◽  
François Lucas
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicles ◽  
User Acceptance ◽  
Mission Planning ◽  
Planning Problem ◽  
Aerial Vehicles ◽  
Mission Duration ◽  
Aerial Vehicle ◽  
Global Planning ◽  
And Control

AbstractUnmanned Aerial Vehicles (UAV) represent a major advantage in defense, disaster relief and first responder applications. UAV may provide valuable information on the environment if their Command and Control (C2) is shared by different operators. In a C2 networking system, any operator may request and use the UAV to perform a remote sensing operation. These requests have to be scheduled in time and a consistent navigation plan must be defined for the UAV. Moreover, maximizing UAV utilization is a key challenge for user acceptance and operational efficiency. The global planning problem is constrained by the environment, targets to observe, user availability, mission duration and on-board resources. This problem follows previous research works on automatic mission Planning & Scheduling for defense applications. The paper presents a full constraint-based approach to simultaneously satisfy observation requests, and resolve navigation plans.

Heterogeneous Aerial Platform Adaptive Mission Planning Using Genetic Algorithms

2017 ◽  
Vol 05 (01) ◽  
pp. 19-30 ◽  
Author(s):  
Jay Wilhelm ◽  
Jonathan Rojas ◽  
Gina Eberhart ◽  
Mario Perhinschi
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Unmanned Aerial Vehicles ◽  
Mission Planning ◽  
Planning System ◽  
Time Increase ◽  
Aerial Vehicles ◽  
Points Of Interest ◽  
Simulation Results

The focus of this study was to examine an automated mission planner that utilized a heterogeneous set of small aerial assets simultaneously surveying several Points of Interest (POI). The concept mission was to aerially search for an unknown Target of Interest (TOI) located amongst a set of POIs. In order to develop a planning system that is capable of meeting mission requirements, an adaptive mission planner, based on a Genetic Algorithm (GA), was investigated that seeks to task a heterogeneous set of unmanned aerial vehicles. Initially, a set of fixed wing UAVs were tasked to survey a set of POIs in search of a TOI, a POI that requires additional or long term surveillance. Once a TOI was located, a multi-rotor UAV was deployed to visit the TOI and additional POIs. Remaining POIs that were not tasked to the multi-rotor UAV were then re-tasked amongst the fixed wing aircraft set. The mission planner was implemented using a GA that planned initial and post TOI identification UAV paths. Mission simulations were conducted and the mission time increase was analyzed against different TOI locations and number of UAVs searching. Simulation results indicated that the deployment of a multi-rotor UAV not only provided additional surveillance of the TOI, but reduced overall mission times as well.

A Flexible Genetic Algorithm System for Multi-UAV Surveillance: Algorithm and Flight Testing

2015 ◽  
Vol 03 (01) ◽  
pp. 49-62 ◽  
Author(s):  
Marjorie Darrah ◽  
Jay Wilhelm ◽  
Thilanka Munasinghe ◽  
Kristin Duling ◽  
Steve Yokum ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Unmanned Aerial Vehicles ◽  
Laboratory Testing ◽  
Field Testing ◽  
Integration Testing ◽  
Flight Testing ◽  
Aerial Vehicles ◽  
Development Laboratory ◽  
Multi Uav

This paper discusses the development and testing of a flexible genetic algorithm (GA)-based system used for tasking a team of unmanned aerial vehicles (UAVs) to complete a coordinated surveillance mission. The GA development, laboratory testing of the GA to ensure convergence to a "good" solution, integration testing with two ground stations, and the field testing of the algorithms are explained. The algorithm was found to be robust and flexible enough to work in various settings with different UAV types and ground stations.

scholarly journals A Flow Analysis Using a Water Tunnel of an Innovative Unmanned Aerial Vehicle

2021 ◽  
Vol 11 (13) ◽  
pp. 5772
Author(s):  
Dawid Lis ◽  
Adam Januszko ◽  
Tadeusz Dobrocinski
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Rapid Development ◽  
Lift Coefficient ◽  
Flow Analysis ◽  
Water Tunnel ◽  
Dual Use ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Technical Construction

The purpose of this article is to present and discuss the results of a non-standard unnamed aerial vehicle construction with a constant cross-section square-shaped avionic profile. Based on the model’s in-air observed maneuverability, the research of avionic construction behavior was carried out in a water tunnel. The results show the model’s specific lift capabilities in comparison to classical avionic constructions. The characteristic results of the lift coefficient showed that the unmanned aerial vehicle presents favorable features than classic avionic constructions. The model was created with the prospect of using it in the future for dual-use purposes, where unmanned aerial vehicles are currently experiencing very rapid development. When creating the prototype, the focus was on low production cost, as well as convenience in operation. The development of this type of breakthrough avionic solution, which shows extraordinary maneuverability, may contribute to increasing the popularity and, above all, the availability of unmanned aerial vehicles for the largest possible group of recipients because of high avionic properties in relation to the technical construction complexity.

scholarly journals A new nonlinear lifting line method for aerodynamic analysis and deep learning modeling of small unmanned aerial vehicles

2021 ◽  
Vol 13 ◽  
pp. 175682932110168
Author(s):  
Hasan Karali ◽  
Gokhan Inalhan ◽  
M Umut Demirezen ◽  
M Adil Yukselen
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Deep Learning ◽  
Unmanned Aerial Vehicles ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Computationally Intensive ◽  
Lifting Line ◽  
Lifting Line Method ◽  
Nonlinear Aerodynamic

In this work, a computationally efficient and high-precision nonlinear aerodynamic configuration analysis method is presented for both design optimization and mathematical modeling of small unmanned aerial vehicles. First, we have developed a novel nonlinear lifting line method which (a) provides very good match for the pre- and post-stall aerodynamic behavior in comparison to experiments and computationally intensive tools, (b) generates these results in order of magnitudes less time in comparison to computationally intensive methods such as computational fluid dynamics. This method is further extended to a complete configuration analysis tool that incorporates the effects of basic fuselage geometries. Moreover, a deep learning based surrogate model is developed using data generated by the new aerodynamic tool that can characterize the nonlinear aerodynamic performance of unmanned aerial vehicles. The major novel feature of this model is that it can predict the aerodynamic properties of unmanned aerial vehicle configurations by using only geometric parameters without the need for any special input data or pre-process phase as needed by other computational aerodynamic analysis tools. The obtained black-box function can calculate the performance of an unmanned aerial vehicle over a wide angle of attack range on the order of milliseconds, whereas computational fluid dynamics solutions take several days/weeks in a similar computational environment. The aerodynamic model predictions show an almost 1-1 coincidence with the numerical data even for configurations with different airfoils that are not used in model training. The developed model provides a highly capable aerodynamic solver for design optimization studies as demonstrated through an illustrative profile design example.

METHODS AND MODELS OF QUALITY MANAGEMENT OF MODULAR DESIGN OF ASSEMBLY PRODUCTION OF UNMANNED AERIAL VEHICLES

2021 ◽  
Author(s):  
E. G. Semenova ◽  
◽  
M. I. Bakustina ◽  
Keyword(s):  
Quality Control ◽  
Quality Management ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Modular Design ◽  
Aerial Vehicles ◽  
Modern Methods ◽  
Aerial Vehicle ◽  
The Creation ◽  
Assembly Production

The article is devoted to the creation of a method for preparing an unmanned aerial vehicle for implementation as a finished packaged product. To achieve the goal, modern methods of standardization and quality control are used.

Modeling and control of a quadrotor tail-sitter unmanned aerial vehicles

2021 ◽  
pp. 095965182110504
Author(s):  
Hongbo Xin ◽  
Yujie Wang ◽  
Xianzhong Gao ◽  
Qingyang Chen ◽  
Bingjie Zhu ◽  
...  
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Euler Angle ◽  
Level Flight ◽  
Aerial Vehicles ◽  
Flight Mode ◽  
Aerial Vehicle ◽  
Hover Flight ◽  
And Control

The tail-sitter unmanned aerial vehicles have the advantages of multi-rotors and fixed-wing aircrafts, such as vertical takeoff and landing, long endurance and high-speed cruise. These make the tail-sitter unmanned aerial vehicle capable for special tasks in complex environments. In this article, we present the modeling and the control system design for a quadrotor tail-sitter unmanned aerial vehicle whose main structure consists of a traditional quadrotor with four wings fixed on the four rotor arms. The key point of the control system is the transition process between hover flight mode and level flight mode. However, the normal Euler angle representation cannot tackle both of the hover and level flight modes because of the singularity when pitch angle tends to [Formula: see text]. The dual-Euler method using two Euler-angle representations in two body-fixed coordinate frames is presented to couple with this problem, which gives continuous attitude representation throughout the whole flight envelope. The control system is divided into hover and level controllers to adapt to the two different flight modes. The nonlinear dynamic inverse method is employed to realize fuselage rotation and attitude stabilization. In guidance control, the vector field method is used in level flight guidance logic, and the quadrotor guidance method is used in hover flight mode. The framework of the whole system is established by MATLAB and Simulink, and the effectiveness of the guidance and control algorithms are verified by simulation. Finally, the flight test of the prototype shows the feasibility of the whole system.

Optimizing Perimeter Surveillance Drones to enhance the security system of unmanned aerial vehicles

2021 ◽  
Vol 2 (2) ◽  
pp. 105-115
Author(s):  
Mahmod Al-Bkree
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Security System ◽  
Small Scale ◽  
Security Systems ◽  
Ongoing Research ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Initial Results

This work is to optimize perimeter surveillance and explore the distribution of ground bases for unmanned aerial vehicles along the Jordanian border and optimize the set of technologies for each aerial vehicle. This model is part of ongoing research on perimeter security systems based on unmanned aerial vehicles. The suggested models give an initial insight about selecting technologies carried by unmanned aerial vehicles based on their priority; it runs for a small scale system that can be expanded, the initial results show the need for at least four ground bases along the length of the border, and a selected set of various technologies for each vehicle.

scholarly journals Identifying Potential Mosquito Breeding Grounds: Assessing the Efficiency of UAV Technology in Public Health

Robotics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 91
Author(s):  
Jared Schenkel ◽  
Paul Taele ◽  
Daniel Goldberg ◽  
Jennifer Horney ◽  
Tracy Hammond
Keyword(s):  
Form Factor ◽  
Unmanned Aerial Vehicles ◽  
Ground Truth ◽  
Gps Receivers ◽  
Aerial Vehicles ◽  
Breeding Grounds ◽  
Aerial Vehicle ◽  
Mosquito Breeding ◽  
Small Form Factor ◽  
Local Transmission

Human ecology has played an essential role in the spread of mosquito-borne diseases. With standing water as a significant factor contributing to mosquito breeding, artificial containers disposed of as trash—which are capable of holding standing water—provide suitable environments for mosquito larvae to develop. The development of these larvae further contributes to the possibility for local transmission of mosquito-borne diseases in urban areas such as Zika virus. One potential solution to address this issue involves leveraging unmanned aerial vehicles that are already systematically becoming more utilized in the field of geospatial technology. With higher pixel resolution in comparison to satellite imagery, as well as having the ability to update spatial data more frequently, we are interested in investigating the feasibility of unmanned aerial vehicles as a potential technology for efficiently mapping potential breeding grounds. Therefore, we conducted a comparative study that evaluated the performance of an unmanned aerial vehicle for identifying artificial containers to that of conventionally utilized GPS receivers. The study was designed to better inform researchers on the current viability of such devices for locating a potential factor (i.e., small form factor artificial containers that can host mosquito breeding grounds) in the local transmission of mosquito-borne diseases. By assessing the performance of an unmanned aerial vehicle against ground-truth global position system technology, we can determine the effectiveness of unmanned aerial vehicles on this problem through our selected metrics of: timeliness, sensitivity, and specificity. For the study, we investigated these effectiveness metrics between the two technologies of interest in surveying a study area: unmanned aerial vehicles (i.e., DJI Phantom 3 Standard) and global position system-based receivers (i.e., Garmin GPSMAP 76Cx and the Garmin GPSMAP 78). We first conducted a design study with nine external participants, who collected 678 waypoint data and 214 aerial images from commercial GPS receivers and UAV, respectively. The participants then processed these data with professional mapping software for visually identifying and spatially marking artificial containers between the aerial imagery and the ground truth GPS data, respectively. From applying statistical methods (i.e., two-tailed, paired t-test) on the participants’ data for comparing how the two technologies performed against each other, our data analysis revealed that the GPS method performed better than the UAV method for the study task of identifying the target small form factor artificial containers.

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