ISI Journals

Mine disasters remain among the most dangerous industrial emergencies due to their extreme environments, limited visibility, structural instability, and high levels of toxic gases. Traditional search and rescue operations, which rely heavily on human responders, are frequently hindered by safety hazards and time-sensitive constraints. In this context, robotics has emerged as a transformative technological frontier that enhances both efficiency and safety in subterranean rescue missions. This paper explores the evolving landscape of robotic platforms designed specifically for mine search and rescue, emphasizing their adaptability to extreme environments, safety engineering integration, and the prospects of intelligent platforms for disaster response. Drawing on prior technological advancements, the study highlights the integration of multi-modal sensing, autonomous navigation, and human– machine interaction systems that increase situational awareness and operational resilience. Smart platforms equipped with machine learning algorithms and real-time data processing are increasingly employed to improve risk assessment, structural analysis, and rapid decision-making. The analysis also underscores the critical role of safety engineering in shaping robot design and deployment strategies, ensuring reliable performance under hazardous conditions. Furthermore, the paper investigates the implications of human–robot collaboration, where autonomous systems complement human expertise, reducing responder exposure to life-threatening risks. Finally, the study considers future directions, including swarming robotics, advanced artificial intelligence, and platform miniaturization, all of which offer significant potential to expand rescue capabilities in unpredictable environments. By providing an integrated perspective on robotics for mine rescue, this research contributes to the broader discourse on resilient disaster-response technologies and underscores the necessity of continuous innovation to safeguard human lives in extreme conditions.