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.

This paper addresses the problem of trajectory planning and tracking control of groups of unmanned vehicles. The trajectory planner is aimed at satisfying the dynamic equations and constraints. The planner builds on two features of the group: (1) state equations for each member are differentially flat, and (2) inequality constraints have special structures due to proximity constraints between members. Under these assumptions, formations are made so that the dynamic equations and constraints are satisfied. Illustrative simulations of groups of unmanned ground vehicles in formations are presented. The results are also implemented on a laboratory facility with three unmanned ground vehicles.