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Design and simulation of autonomous military vehicle control system based on machine vision and ensemble movement approach

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Abstract

On the battlefield, early detection of armored vehicles can have a positive effect. Because according to this issue, timely and appropriate reactions can be done. The purpose of this study is to achieve the required algorithm in the vehicle control system by considering the car sensor vision, which is necessary to identify and determine the equipment needed to control the military drone based on car sensor vision. Today, the use of wireless networks, especially inter-vehicle wireless networks, in military applications is inevitable. Therefore, in the first step of this research, a new method has been proposed to control and steer unmanned vehicles based on car vision. In the proposed method, two 180-degree panoramic cameras with horizontal vision are used from the recorded images. The simulation results of the proposed method show increased accuracy and reduced implementation cost compared to using LIDAR and RADAR technologies. In the second step, a new approach is introduced to identify four common classes of armored vehicles (tanks, personnel carriers, firing tanks, and military vehicles) that are more likely to be present on battlefields. For this purpose, the latest image processing methods, which is deep learning, have been used. The results of the simulation of the proposed approach show the high accuracy of the proposed approach in detecting armored vehicles in a short time. In the third step of this research, a new method has been proposed to increase the connection of wireless networks. In the proposed method, queue theory is used and the results of the simulation of the proposed method show the high efficiency of the method. As a result, accurate and fast detection with unique features makes the users of the system superior.

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  1. Department of Electrical and Computer Engineering, Malek-Ashtar University of Technology, Tehran, Iran

    Kourosh Dadashtabar Ahmadi, Ali Jabar Rashidi & Ali Massomi Moghri

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  1. Kourosh Dadashtabar Ahmadi
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  2. Ali Jabar Rashidi
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  3. Ali Massomi Moghri
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Correspondence to Ali Massomi Moghri.

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Ahmadi, K.D., Rashidi, A.J. & Moghri, A.M. Design and simulation of autonomous military vehicle control system based on machine vision and ensemble movement approach. J Supercomput 78, 17309–17347 (2022). https://doi.org/10.1007/s11227-022-04565-6

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  • DOI: https://doi.org/10.1007/s11227-022-04565-6

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