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Authors: Protasov V., Mirakhmedov R., Potapova Z.     Published in № 6(108) 25 december 2023 year
Rubric: Models and methods

Using molecular dynamics method for a decentralized UAV autonomous self-governance system

A computer model and test results of a decentralized self-controlling UAV system using the molecular dynamics method and various forms of interaction potential are presented. In this model, each UAV is replaced by a “quasi-molecule” with point dimensions and a mass equal to the mass of the UAV. The motion of these “quasi-molecules” is calculated using Newtonian mechanics, taking into account the potential force field from other “quasi-molecules”. The system consists of a group of UAVs performing various ordered formations in accordance with a given mission, as well as obstacles and “hunters” trying to collide with the UAV. “Hunters” are also represented by point-like “quasi-molecules”. This allows us to simulate the presence in the system of both active and passive interference with UAV movement. When modeling passive interference, “hunters” are located on the surface of an obstacle at the nodes of a surface mesh superimposed on it. When modeling the movement of UAVs, taking into account their interaction with each other, active and passive interference, specially designed interaction potentials were used. Numerous tests have been carried out on the system under these conditions. No collisions of the UAVs with each other, with obstacles or with “hunters” were observed. This confirms the reliability of the developed principles for controlling the movement of a group of UAVs under conditions of intense active and passive interference. The main difference between the presented work and existing ones is that various missions are carried out by groups of UAVs without external control according to data from a technical 3D vision system within the framework of a fairly simple molecular dynamics model by changing the shape of interaction potentials.

Key words

UAV self-governance, UAV formations, active interference, collective intelligence, computer modeling, molecular dynamics method, interaction potential

The author:

Protasov V.

Degree:

Dr. Sci. (Eng.), Associate Professor, Professor of Department 307, Moscow Aviation Institute (National Research University)

Location:

Moscow, Russia

The author:

Mirakhmedov R.

Degree:

Postgraduate, Department 311, Moscow Aviation Institute (National Research University)

Location:

Moscow, Russia

The author:

Potapova Z.

Degree:

Cand. Sci. (Phys.-Math.), Associate Professor, Department 804, Moscow Aviation Institute (National Research University)

Location:

Moscow, Russia