Design of an Autonomous Cruising Scheme for Carrier-Based Aircraft Based on Machine Vision

In recent years, with the continuous development of computer and unmanned control technology, and due to the low cost and high safety of drones, they have been widely used in various fields. As an unmanned aerial vehicle, drones can effectively reduce casualty rates in military applications and have important advantages as military weapons, making them an indispensable strategic force in the field of military operations. Carrier-based drone technology has become an important means for strike and reconnaissance missions. However, current drones mostly use GPS positioning and remote control to fly, which cannot achieve intelligent cruising and are limited by GPS signal accuracy. To improve the cruising efficiency and automation level of airborne drones, this paper proposes an autonomous cruising system based on machine vision combined with inertial sensors that utilizes visual altitude information of a single known point landmark to estimate the position and speed of the cruising drone. The system uses visual assistance to achieve long-duration flight and positioning and cruising by fusing data collected from multiple groups of infrared sensors, ultrasonic sensors, barometric sensors, and inertial sensors. The results of simulation experiments also demonstrate the effectiveness of the method proposed in this paper, with certain feasibility.