Delayed Kalman filter for vision-based autonomous flight in ocean environments

Abstract

This paper presents the developments of flight hardware and software for a multirotor unmanned aerial vehicle, performing autonomous take-off and landing on a moving vessel in ocean environments. The proposed flight hardware is composed of a general-purpose computing module connected to a low-cost inertial measurement, an real-time kinematics GPS, motor speed controller, and a camera, through a custom-made printed circuit board. The flight software is developed in C++ with multi-threading such that the multiple tasks of control, estimation, and communication are executed simultaneously. The proposed flight system is verified with autonomous flight experiments on a United States Naval Academy research vessel operating in Chesapeake Bay. Two types of flight experiments are performed: autonomous flight utilizing real-time kinematics GPS for relative positioning, and vision-based autonomous flight, both for shipboard launch and landing.