STM32-Based Landmine Detection and GPS Localization Robotic Vehicle

Autonomouslandmine detection remains a majorsafety challenge, as conventional manual methods expose personnel to hazardous environments, take considerable time, and may offer limited spatial tracking of detected threats. These limitations are particularly significant in military, humanitarian demining, and hazardous-terrain operations where accurate localization, autonomous navigation, and real-time monitoring are required. This thesis presents an Autonomous GNSS-Guided Mine Detection and Geofenced Monitoring Robot designed to autonomously survey a defined area and identify and spatially record potential metallic mine locations. The system provides dedicated access for field operators and administrators, where operators monitor robot movement, detected targets, and surveyed regions while administrators manage operational data, geofencing, and monitoring functions. The core mechanism combines GNSS positioning with centimeter-level correction, geofencing, barometric sensing, metal detection, and motor control to continuously calculate robot position and constrain movement within the predefined boundary, providing transparent rule-based navigation rather than relying on a black-box navigation model. Supporting features include autonomous movement, virtual fencing, boundary violation prevention, metal-detection marking, real-time position tracking, sensor-status monitoring, location logging, historical data visualization, and remote dashboard monitoring.