Improving self-localization efficiency in a small mobile robot by using a hybrid field of view vision system

Abstract

In this article a self-localization system for small mobile robots based on inexpensive cameras and unobtrusive, passive landmarks is presented and evaluated. The main contribution is the experimental evaluation of the hybrid field of view vision system for self-localization with artificial landmarks. The hybrid vision system consists of an omnidirectional, upward-looking camera with a mirror, and a typical, front-view camera. This configuration is inspired by the peripheral and foveal vision co-operation in animals. We demonstrate that the omnidirectional camera enables the robot to detect quickly landmark candidates and to track the already known landmarks in the environment. The front-view camera guided by the omnidirectional information enables precise measurements of the landmark position over extended distances. The passive landmarks are based on QR codes, which makes possible to easily include in the landmark pattern additional information relevant for navigation. We present evaluation of the positioning accuracy of the system mounted on a SanBot Mk II mobile robot. The experimental results demonstrate that the hybrid field of view vision system and the QR code landmarks enable the small mobile robot to navigate safely along extended paths in a typical home environment.