Stereo Parallel Tracking and Mapping for Robot localization

TAIHÚ PIRE; THOMAS FISCHER; JAVIER CIVERA; PABLO DE CRISTÓFORIS; JULIO JACOBO BERLLES

Hamburgo

Conferencia; 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS); 2015

https://doi.org/10.1109/IROS.2015.7353546

This paper describes a visual SLAM system based on stereo cameras, focused on real-time localization for mobile robots. To achieve this, it heavily exploits the parallel nature of the SLAM problem, separating the time-constrained pose estimation from less pressing matters such as map building and refinement tasks. On the other hand, the stereo setting allows to reconstruct a metric 3D map for each frame of stereo images, improving the accuracy of the mapping process with respect to monocular SLAM and avoiding the well-known bootstrapping problem. Also, the real scale of the environment is an essential feature for robots which have to interact with their surrounding workspace. A series of experiments, on-line on a robot as well as off-line with public datasets, are performed to validate the accuracy and real-time performance of the developed method.