Abstract

This paper describes a visual SLAM system based on stereo cameras and 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.

Keywords

Computer visionArtificial intelligenceComputer scienceSimultaneous localization and mappingRobotStereo camerasMobile robotMetric (unit)Feature (linguistics)MonocularProcess (computing)StereopsisEngineering

Affiliated Institutions

Related Publications

Publication Info

Year
2015
Type
article
Pages
1373-1378
Citations
118
Access
Closed

External Links

View on DOI.org

Social Impact

Altmetric
PlumX Metrics

Social media, news, blog, policy document mentions

Citation Metrics

118
OpenAlex

Cite This

Taihú Pire, Thomas Fischer, Javier Civera et al. (2015). Stereo parallel tracking and mapping for robot localization. , 1373-1378. https://doi.org/10.1109/iros.2015.7353546

Identifiers

DOI
10.1109/iros.2015.7353546