THE SYNTHESIS OF ROUTES OF UAVS’ SUB-SWARMS BASED ON HOPFIELD NEURAL NETWORK FOR INSPECTION OF TERRITORIES

I. M. Zhuravska, M. P. Musiyenko

Abstract


Context. The urgent task the economy of the limited power, computing and technological resources of small unmanned aerial vehicles (UAVs) has been solved.

Objective is a creation of sub-swarms’ routes synthesis method with increasing the time of UAV flock viability.

Method. The method for model building of the UAVs’ sub-swarm is offered. It allows to avoid the dubbed tasks at any node of grids that cover the survey territory. Combining Hopfield neural network’s map and flight map for each sub-swarm provides an information via wireless communication modules of UAV about the executed facts of monitoring or technological tasks by any individual UAV of sub-swarm to rest of UAVs. This approach allows to use the self-healing properties of the sub-swarms in flocks of bird-like objects (“boids”) by means redefining the tasks of sub-swarms as a cyber-physical system in case of loss of several boids during a critical usage. The structure of the resulting sub-swarms’ behavior models is implemented in two-dimensional spatial corridors of arbitrary shape; then achieved 2D-solving are concatenated. This can significantly speed up the tasks survey territories.

Results. The software implementing proposed method have been developed and used in computational experiments investigating the properties of the method. The experiments confirmed the efficiency of the proposed method and software.

Conclusions. The experiments also allow to recommend them for use in practice to solve the problems survey area using boids’ flock.

Keywords


Unmanned air vehicle; sub-swarm; flock; Hopfield neural network; dubbed tasks.

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DOI: https://doi.org/10.15588/1607-3274-2017-3-10



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