SLAM Algorithm by using global appearance of omnidirectional images
Y. Berenguer, L. Payá, A. Peidró, O. Reinoso
Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2017)  (Madrid (SPAIN), 26-28 July 2017)
Ed. SCITEPRESS  - Vol. 2, pp. 382-388

Resumen:



This work presents a SLAM algorithm to estimate the position and orientation of a mobile robot while simultaneously



creating the map of the environment. It uses only visual information provided by a catadioptric system



mounted on the robot formed by a camera pointing towards a convex mirror. It provides the robot with omnidirectional



images that contain information with a field of view of 360 degrees around the camera-mirror axis.



Each omnidirectional scene acquired by the robot is described using global appearance descriptors. Thanks to



their compactness, this kind of descriptors permits running the algorithm in real time. The method consists of



three different steps. First, the robot calculates the pose of the robot (location and orientation) and creates a



new node in the map. This map is formed by connected nodes between them. Second, it detects loop closures



between the new node and the nodes of the map. Finally, the map is optimized by using an optimization



algorithm and the detected loop closures. Two different sets of images have been used to test the effectiveness



of the method. They were captured in two real environments, while the robot traversed two paths. The results



of the experiments show the effectiveness of our method.