Robust Motion Estimation Based on Multiple Monocular Camera for Indoor Autonomous Navigation of Micro Aerial Vehicle

This paper is focusing on the development of a system based on computer vision to estimate the movement of an MAV (X, Y, Z and yaw). The system integrates elements such as: a set of cameras, image filtering (physical and digital), and estimation of the position through the calibration of the system and the application of an algorithm based on experimentally found equations. The system represents a low cost alternative, both computational and economic, capable of estimating the position of an MAV with a significantly low error using a scale in millimeters, so that almost any type of camera available in the market can be used. This system was developed in order to offer an affordable form of research and development of new autonomous and intelligent systems for closed environments.