Multi-sensor navigation system for an autonomous helicopter

Autonomous Unmanned Aerial Vehicles (UAVs) require avionics systems that enable them to maintain a stable attitude and to follow a desired flight path. This paper considers the design and development of such an avionics system that provides navigational and terrain information to the flight computer of a rotorcraft UAV. The process includes the design and testing of flight hardware and software that interprets sensor data. The paper provides an overview of a specific implementation of the approach: the GTMax testbed developed at the Georgia Institute of Technology UAV Research Facility. Its available payload and performance allows for a variety of onboard sensors, supports reconfiguration, and has the capability to demonstrate aggressive maneuvers under complex and changing mission scenarios. First, the hardware selection and integration process will be outlined. The design factors include weight, electromagnetic interference, vibration, flexibility, hardware integration, redundancy, maintainability, and growth potential. Sensor data from multiple sources is filtered and integrated/fused into a navigation solution. Before actual flight tests take place, sensor interfaces and navigation algorithms are verified to ensure proper functioning. By using software emulated sensor data and a simulation model of the aircraft, the algorithms are first tested. The same test is then repeated on the actual flight computer by feeding simulated sensor data from a computer that is running a simulation model of the vehicle and sensors. The navigation system is then tested on the ground in an automobile, and then on the helicopter. Ground and flight-test data showing sensor and navigation system performance are compared to simulation results.