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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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...
Biobjective route planning of an unmanned air vehicle in continuous space
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We consider the route planning problem of an unmanned air vehicle (UAV) in a continuous space that is monitored by radars. The UAV visits multiple targets and returns to the base. The routes are constructed considering the total distance traveled and the total radar detection threat objectives. The UAV is capable of moving to any point in the terrain. This leads to infinitely many efficient trajectories between target pairs and infinitely many efficient routes to visit all targets. We use a two stage approa...
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: