International Research Journal of Engineering and Technology (IRJET) Volume: 12 Issue: 11 | Nov 2025 www.irjet.net
e-ISSN: 2395-0056 p-ISSN: 2395-0072
AI-ENHANCED AUTONOMOUS MILITARY ROBOT FOR MINE DETECTION AND THREAT IDENTIFICATION Ishu M1, Mr Sathish Kumar M2 1Pg Student, Department Of Computer Applications, Jaya College Of Arts and Science, Thiruninravur,
Tamilnadu,India 2Assistant Professor,Department Of Computer Applications, Jaya College Of Arts and Science, Thiruninravur,
Tamilnadu,India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract - The development of an advanced autonomous 2.LITERATURE SURVEY military robot that employs artificial intelligence (AI) and deep learning (DL) techniques for mine detection and threat identification. The machine learning model, trained to recognize mine patterns, allows the robot to identify potential threats through image analysis. Upon detection, the system provides precise latitude and longitude coordinates of the mine's location. Utilizing its trained deep learning model, the robot can identify and capture images of individuals displaying threatening behavior.This project introduces an AI-enhanced autonomous military robot designed for mine detection and threat identification. Using artificial intelligence, sensors, and computer vision, the robot can navigate, detect, and identify threats with high accuracy. It reduces human risk, improves mission safety, and provides a smart, reliable solution for military operations in hazardous areas.
Tittle: Mine Detection using a Swarm of Robots Year Published: 2020 Journal Name: IEEE Author Name: Luca Bossi, Pierluigi Falorni, Gennadiy Pochanin,Timothy Bechtel, Jack Sinton,Fronefield Crawford Proposed Method in the paper:In this paper they have only used the sensors to detect the landmines while ysing the Sensor there will be a list of Problems like Accuracy,range etc...so we have Integrated the camera with that. Advantage:I this paper we have worked to improve the Accuracy of the detection of the landmines in the war fields. Recent studies show that AI and robotics are increasingly used for mine detection and threat identification in military operations. Existing systems use sensors and machine learning for detection but struggle in complex terrains. This project improves these methods by integrating AI, sensor fusion, and computer vision for safer and more accurate threat detection.
Key Words: Autonomous mine detection robot, AI mine detection, explosive ordnance detection, threat identification robot, autonomous EOD system
1.INTRODUCTION
3.Methodology
The rapid advancement of Artificial Intelligence (AI) and robotics has revolutionized modern defense technologies, enabling the development of intelligent and autonomous systems for critical military operations. One of the most significant applications of such technology is in mine detection and threat identification, where human involvement often poses severe risks. Traditional methods of landmine and explosive detection rely heavily on manual operations or remotely controlled vehicles, which are both time-consuming and hazardous.The AI-enhanced autonomous military robot is developed to perform mine detection and threat identification in dangerous areas. By combining artificial intelligence, sensors, and computer vision, it can detect landmines and identify threats without human risk. This technology improves safety, accuracy, and efficiency in modern military operations.
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The robot uses AI algorithms, sensors, and camera modules to detect objects and obstacles. It employs sensor fusion for mine detection and image processing for threat identification. The robot’s microcontroller processes data and enables autonomous movement and decision-making.
4.Existing system Metal Sensor: The existing system mainly relies on metal sensors to detect landmines. However, this method is not highly efficient as it can produce false alarms due to the presence of metallic debris. Manual or Semi-Autonomous Control: Movement and detection are often manually operated or semiautonomous, requiring human supervision for navigation and decision-making.
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