Vision-Based Qualitative Path-Following Control of Quadrotor Aerial Vehicle with Speeded-Up Robust Features

Abstract

This paper describes a vision-based 3D navigation technique for path-following control of Quad rotor Aerial Visual-Teach-and-Repeat system. The navigation method is developed on Funnel Lane theory, which defines possible positions to fly straight. The navigation calculation utilizes the reference images and features to compute the desired heading angle and height during path following. The type of feature is Speeded-Up Robust Features (SURF). The tracking feature method between images is performed by matching SURF feature's descriptors. The Quad rotor is able to independently perform path following in indoor environment without the support of an external tracking system. Simulation is conducted on Robot Operating System (ROS) and Gazebo simulator. The application of the proposed method is visual-homing and visual-servoing in GPS-denied environment.