Autonomous Micro Aerial Vehicle Flight Using Optical Flow and Inertial Cues

Micro aerial vehicles (MAVs) are agile and have unstable flight dynamics. They require a failsafe method to be navigated through areas even without GPS coverage. The approach of this work is to use only the feature matches between two consecutive images, i.e. optical flow (OF) and inertial cues. The vehicle’s pose and additional intrinsic as well as extrinsic states are estimated continuously to navigate and control the MAV through the area. Optical flow cues and inertial measurement readings are fused in an EKF (extended Kalman filter) framework to estimate a metric 3D body velocity, terrain plane-parameters, terrain plane relative 3D attitude including heading, and metric distance between the camera on the MAV and this plane. The estimates of the EKF provide the vehicle controller with accurate information about the vehicle and the environment in order to navigate the micro-helicopter autonomously through large areas. The system is fully self-contained and all computation is done onboard the MAV in real-time. This eliminates the need of a data link to a ground station and allows standalone operation.