This project had two objectives related to operation of drone swarms in GPS-denied environments: (1) the development of a structured model of environmental deviance to aid in autonomous navigation, and (2) the integration of such a model into a collision avoidance system. Both of these objectives were achieved and the outcomes were tested in the framework of a simulated environment that mimics a GPS-denied scenario. Using data from hundreds of simulated swarm flights, the obtained findings indicated that structured learning can improve navigational accuracy without the need for externally provided position feedback.