Seamless Fusion: Multi-Modal Localization for First Responders in Challenging Environments

Area of Science:

• Robotics and Sensor Fusion
• Geomatics Engineering
• Emergency Response Technology

Background:

• Precise localization of first responders is critical in dynamic environments.
• Existing localization methods often fail indoors or rely on external infrastructure.
• Responder safety and operational effectiveness depend on reliable positioning.

Purpose of the Study:

• To develop and validate a novel, infrastructure-free fused localization system for first responders.
• To integrate visual, Galileo (GNSS), and inertial sensor data for robust positioning.
• To achieve accurate and seamless indoor and outdoor localization capabilities.

Main Methods:

• Visual-based localization using RGB camera and ORB-SLAM2.
• Galileo-based localization with a high-accuracy GNSS receiver prototype.
• Inertial-based localization via smartphone inertial measurement units (IMUs) for sensor fusion.
• Fusion of the three modalities to create a comprehensive localization tool.

Main Results:

• The fused localization tool provides continuous positioning across diverse environments (indoor/outdoor).
• The system demonstrates robustness, functioning without reliance on pre-existing infrastructure.
• Achieved an overall mean localization error of 1.73 meters.

Conclusions:

• The proposed fused localization system offers a reliable and accurate solution for first responders.
• This technology enhances responder safety and operational effectiveness in unpredictable scenarios.
• The infrastructure-free approach ensures consistent performance regardless of environmental conditions.