Vision-aided inertial navigation on an uncertain map using a particle filter

This paper presents a vision-based navigation solution for unmanned aircraft operations on airfield surfaces in GPS-denied environments. The unmanned aircraft system ground operations management system (UGOMS) described here combines measurements from a computer vision system and inertial sensors with an airport layout database to provide real-time position determination on the airfield surface. UGOMS provides both absolute position of the aircraft as well as relative position to airport surface elements such as runway hold lines and taxiway edges. The key technical components of UGOMS are computer vision algorithms that classify image regions, Markov localization using particle filters, and a navigation architecture which incorporates the localization information. An overview of the overall UGOMS architecture is presented as well as preliminary test results using an uncertain airfield map to highlight the performance capabilities of the system.