Computer Vision News - October 2019

8 Research To better understand the quality of the method we also include a table of quantitative results that compare the average position error in cm and the running time in ms: Conclusion The problem of localization and mapping is crucial for many robotics and vision application. GSLAM introduces a novel global approach for solving Simultaneous Localization andMapping problems as opposed tomost of the current methods which use incremental schemes. The paper demonstrates high-quality results including improvement of the current state of the art results. The applications that need accurate localization are evolving more rapidly than the developments in this field and, for this reason, we believe that SLAM is here to stay!