CONCEPTUAL MODEL OF A DISTRIBUTED HUMANITARIAN DEMINING SYSTEM BASED ON SWARM INTELLIGENCE AND MACHINE LEARNING

Abstract

This article provides an analysis of the challenges and emerging trends in humanitarian demining, emphasizing the transformative potential of unmanned solutions and artificial intelligence. The escalating complexity of contaminated areas necessitates a shift from manual detection to automated, high-precision systems. The central contribution of this research is the development of a conceptual model for a distributed system that utilizes a heterogeneous unmanned systems network. Such a network based on swarm of unmanned aerial vehicles (UAV), ground robotic complexes (GRC) and coordinated through remote control station, creates a framework for autonomous site survey and unexploded ordnances (UXO) identification.

A significant portion of the study is dedicated to the application of deep learning algorithms in the recognition of explosive ordnance (EO). The paper highlights the critical relevance of Convolutional Neural Networks (CNNs) as the industry standard for spatial feature extraction and real-time object detection. Additionally, the research finds promising potential of hybrid deep machine learning models and multimodal AI models.

Modern UAVs and GRCs are increasingly designed as versatile carriers capable of hosting a wide array of equipment, ranging from high-resolution optical and thermal sensors to active induction tools and ground-penetrating radars. Installing magnetometers, hyperspectral cameras, LiDAR – allows for a multi-layered data acquisition strategy which opens opportunities for distributed systems containing various unmanned vehicles with special sensors.

The study also emphasizes the importance of demining operator safety. Shifting the UXO detection and neutralization burden to autonomous drone swarms removes human deminers from high-risk zones. The article concludes that the transition toward distributed, heterogeneous autonomous systems, powered by machine learning, represents one the most viable path for the future of humanitarian demining.