A behaviour tree-based robust decision framework for enhanced UAV autonomy

An enhanced level of autonomy for UAVs is desirable when behaviours more sophisticated than simply following waypoint presets are desired. Behaviour Trees (BT) provide a decision tree like approach for developers to efficiently implement these sophisticated behaviours through a robust, modular, scalable framework. This paper presents a framework for easy development of BTs which implements autonomous unmanned aerial vehicle (UAV) behaviours, building upon the existing Java Behaviour Tree (JBT) software for video games. Behaviour Engine software was also developed, allowing the BTs to be interfaced with an autopilot to deliver enhanced UAV control. The Behaviour Engine software was loaded with BTs implementing the UAV behaviours of pursue, evade, stalk and patrol, with the results showing that these behaviours function as desired in the Behaviour Engine software for two simulated UAVs