Computer Vision for MAVs

Kurzfassung

This chapter discusses recent advances in the use of computer vision for the control of micro aerial vehicles (MAVs). It provides a brief overview of system design and sensors of a MAV. The system design described is from the Pixhawk MAV platform. In most approaches, ego-motion estimation is achieved by fusing information from an inertial measurement unit (IMU) with visual measurements. State estimation is a filtering approach using an extended Kalman filter (EKF) for fusing inertial and vision measurements. The vehicle pose is represented by the pose of the IMU within the world coordinate frame. The camera sensor is the offset of the IMU coordinate frame by a rotation and translation. The big advantage of stereo vision is that the metric scale of camera poses and 3D points can be computed directly. The use of optical flow for controlling MAVs has been popularized with the appearance of Parrot's AR Drone.