Autonomous Guidance for Unmanned Aircraft Operating in National Airspace

Period of Performance: 05/12/2008 - 03/12/2009


Phase 1 SBIR

Recipient Firm

Data Research & Analysis Corp.
1555 King St. #300
Alexandria, VA 22314
Principal Investigator


This document proposes to develop, test, and demonstrate collision avoidance and autopilot guidance algorithms for small unmanned aircraft systems. This project will develop real-time, multithreaded algorithms that will process sensor inputs, manage priorities, plan aircraft trajectories, and generated autopilot inputs. The project will also involve an extensive modeling and simulation effort, in order to perform tests and demonstrations of the algorithms developed. The resulting simulation capability may also be useful for testing alternative algorithms, and for developing and refining system requirements and specifications. UAVs with autonomous capabilities are essentially flying robots. As robots, they need to gather information (sensory input) about the environment around them and make decisions about what they should be doing (controlling actuators or devices). Sensors and devices must be dealt with concurrently, otherwise devices can get starved and sensors ignored. The software design is patterned after the latest generation robotic software. To support testing and validation, a simulation testbed based on the USAF EAAGLES toolkit will be used. This will allow testing in a high-density environment. EAAGLES was built to support distributed simulation so that many EAAGLES-based applications can be executed simultaneously thereby generating many players without compromising performance.