Delay and dropout tolerant state estimation for MAVs

Abstract

This paper presents a filter based position and velocity estimation for an aerial vehicle fusing inertial and delayed, dropout-susceptible vision measurements, without the a priori knowledge of the exact variable time delay. The data from the two sensors, which are running at different rates, is transmitted via independent wireless links to a ground station. A synchronization between both communication ways makes it possible to determine the image transmission and processing time. The computational complexity of the algorithm is kept at a low level. The images are processed by a Visual SLAM algorithm that builds up a map of the area and simultaneously tracks the pose of the camera. With a delay going up to 230 ms and an amount of 16% dropout in the vision data, we show that with the presented filter a quadrotor can be stabilized and kept in the region of a setpoint with a simple PID controller.