As reliance on GPS grows, so do the challenges: signal jamming, urban canyons, dense forests, and underground environments can all render traditional positioning unreliable or unavailable. This session introduces a transformative approach to geospatial problem-solving—leveraging computer vision, precomputed satellite datasets, and advanced sensor fusion to deliver precise, GPS-independent positioning for land and air applications.
Drawing on real-world deployments across urban, remote, and contested environments, we will showcase how Skyline Nav AI’s Pathfinder™ software uses pixel-level image analysis, terrain feature detection, and intelligent integration of camera and IMU data to achieve absolute, real-time localization—without any dependence on GPS, cellular, or Wi-Fi connectivity. Attendees will learn how this workflow enables robust navigation in scenarios where conventional solutions fail, including disaster response, military operations, and autonomous systems.
We will explore:
- Innovative data acquisition and processing workflows that combine satellite imagery, lidar, and real-time visual data.
- Case studies demonstrating successful deployments in urban canyons, mountainous regions, and GPS-denied zones.
- The impact of scalable, software-based navigation on operational resilience, cost, and mission success.
- Lessons learned in integrating multi-sensor data and overcoming challenges of changing terrain and adverse weather.
This session is designed for geospatial professionals seeking actionable insights into next-generation navigation, reality capture, and the practical convergence of computer vision and remote sensing.
