Coordinated guidance for multiple UAVs

Cakici, Ferit
Ergezer, Halit
Irmak, Ufuk
Leblebicioğlu, Mehmet Kemal
This paper addresses the path planning problem of multiple unmanned aerial vehicles (UAVs). The paths are planned to maximize collected amount of information from desired regions (DRs), while avoiding forbidden regions (FRs) and reaching the destination. This study focuses on maximizing collected information instead of minimizing total mission time, as in previous studies. The problem is solved by a genetic algorithm (GA) with the proposal of novel evolutionary operators. The initial populations are generated from a seed-path for each UAV. The seed-paths are obtained both by utilizing the pattern search method and by solving the multiple-Traveling Salesman Problem (mTSP). Utilizing the mTSP solves both the visiting sequences of DRs and the assignment problem of which DR should be visited by which UAV?' All of the paths in the population in any generation of the GA are constructed using a dynamical UAV model. Simulations are realized in a MATLAB/Simulink environment for different mission scenarios and the results provide physically realizable flight paths, which visit DRs and avoid FRs. Real-world experiments are conducted by using small UAVs, which are constructed by autopilot integration on model airplanes. Flight tests performed based on simulated scenarios proved beneficial in maximizing the collected amount of information for multiple UAV missions.


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Unmanned aerial vehicles (UAVs) domain has seen rapid developments in recent years. As the number of UAVs increases and as the missions involving UAVs vary, new research issues surface. An overview of the existing research areas in the UAV domain has been presented including the nature of the work categorised under different groups. These research areas are divided into two main streams: Technological and operational research areas. The research areas in technology are divided into onboard and ground techno...
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Detection and distance estimation of micro unmanned aerial vehicles (mUAVs) is crucial for (i) the detection of intruder mUAVs in protected environments; (ii) sense and avoid purposes on mUAVs or on other aerial vehicles and (iii) multi-mUAV control scenarios, such as environmental monitoring, surveillance and exploration. In this article, we evaluate vision algorithms as alternatives for detection and distance estimation of mUAVs, since other sensing modalities entail certain limitations on the environment...
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© 2022 Elsevier LtdWe address the route planning problem of an unmanned air vehicle (UAV) tasked with collecting information from a radar-monitored environment for a reconnaissance mission. The UAV takes off from a home base, visits a set of targets, and finishes its movement at a final base. Collectable information at a target depends on the time the target is visited by the UAV. There are multiple trajectory alternatives between the target pairs with different travel time and threat attributes. A route pl...
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Tarakçı, Koray; Karasakal, Esra; Karasakal, Orhan; Department of Industrial Engineering (2021-12-10)
In this study, we develop models and solution approaches for planning the surveillance mission of a homogeneous fleet of Unmanned Aerial Vehicles (UAVs). Predefined areas are to be observed while satisfying a minimum probability of target detection. Areas are assumed to be rectangular and discrete. UAVs with electro-optical sensors take off from a base and fly through predefined routes. The endurance of UAVs is limited by the maximum flight distance. The proposed models minimize the total travel distance of...
Interactive approaches for bi-objective UAV route planning in continuous space
Türeci, Hannan; Köksalan, Murat; Tezcaner Öztürk, Diclehan; Department of Industrial Engineering (2017)
We study the route planning problem of unmanned air vehicles (UAVs). We consider two objectives; minimizing total distance traveled and minimizing total radar detection threat since these objectives cover most of the other related factors. We consider routing in a two-dimensional continuous terrain, in which we have infinitely many efficient trajectories between target pairs. We develop interactive algorithms that find the most preferred solution of a route planner (RP), who has either of the underlying pre...
Citation Formats
F. Cakici, H. Ergezer, U. Irmak, and M. K. Leblebicioğlu, “Coordinated guidance for multiple UAVs,” TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, pp. 593–601, 2016, Accessed: 00, 2020. [Online]. Available: