Embry-Riddle Aeronautical University (ERAU) and Creare LLC are developing an advanced autonomous flight control system to navigate unmanned aerial vehicles (UAVs) in unknown dynamic environments, such as urban environments. The system leverages recent developments in small, low-power, and low-cost sensor technology and improved computer hardware, along with high performance guidance, navigation, and control (GNC) algorithms.
The autonomous GNC system under development by ERAU includes vision-based algorithms for improved navigation in GPS-denied environments, 3-D terrain algorithms to generate an adaptive terrain map from processed vision and LIDAR sensor data, and receding horizon algorithms to adaptively plan a 3-D path through the environment with obstacle avoidance. A bio-inspired, fault-tolerant flight control system is being developed to autonomously fly the vehicle along the planned path subject to disturbances such as wind gusts. The flight control system is designed to compensate for potential system failures such as sensor or actuator failures. The GNC system will also incorporate reactive obstacle avoidance algorithms to sense and avoid dynamic obstacles in the scene.
To support this research effort, ERAU has instrumented a SkyJib quadcopter UAV with a sensor suite that includes monocular and stereo cameras, an infrared camera, a scanning LIDAR, and an inertial navigation system (INS) with GPS. This UAV served as a test platform for data collection during the Phase I program, and it will be used for GNC system development and validation during the Phase II program. ERAU has also developed a high fidelity simulation environment to simulate autonomous UAV flight in virtual urban environments. The simulator includes detailed 6 degree-of-freedom UAV models, sensor models, and hardware-in-the-loop simulation capability. This simulation environment serves as an important tool for GNC system development and validation as well as the development of real-time processing algorithms.