- Autonomous navigation in 2D and 3D environments has been studied for a long time. Navigating within a 3D environment is very challenging for both animals and robots and a variety of sensors are used to solve this task ranging from vision or a simple gyro or compass to GPS. The principal tasks for 3D autonomous navigation are course stabilization, altitude and drift control, and collision avoidance. Using this basis, some features can be easily added like aerial mapping, object recognition, homing strategies or takeoff and landing. Here we present a biologically based control layer for an Unmanned Aerial Vehicle (UAV) that provides course stabilization, altitude and drift control, and collision avoidance. The properties of this neuronal control system are evaluated using a flying robot.
Sergi Bermúdez i Badia, Pawel Pyk, Paul F.