Data Association Using Visual Object Recognition for EKF-SLAM in Home Environment
- 1 October 2006
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 21530858,p. 2588-2594
- https://doi.org/10.1109/iros.2006.281936
Abstract
Reliable data association is crucial to localization and map building for mobile robot applications. For that reason, many mobile robots tend to choose vision-based SLAM solutions. In this paper, a SLAM scheme based on visual object recognition, not just a scene matching, in home environment is proposed without using artificial landmarks. For the object-based SLAM, the following algorithms are suggested: 1) a novel local invariant feature extraction by combining advantages of multi-scale Harris corner as a detector and its SIFT descriptor for natural object recognition, 2) the RANSAC clustering for robust object recognition in the presence of outliers and 3) calculating accurate metric information for SLAM update. The proposed algorithms increase robustness by correct data association and accurate observation. Moreover, it also can be easily implemented real-time by reducing the number of representative landmarks, i.e. objects. The performance of the proposed algorithm was verified by experiments using EKF-SLAM with a stereo camera in home-like environments, and it showed that the final pose error was bounded after battery-run-out autonomous navigation for 50 minutesKeywords
This publication has 7 references indexed in Scilit:
- A performance evaluation of local descriptorsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- CV-SLAM: a new ceiling vision-based SLAM techniquePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Distinctive Image Features from Scale-Invariant KeypointsInternational Journal of Computer Vision, 2004
- Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual LandmarksThe International Journal of Robotics Research, 2002
- Robust Mapping and Localization in Indoor Environments Using Sonar DataThe International Journal of Robotics Research, 2002
- Optimization of the simultaneous localization and map-building algorithm for real-time implementationIEEE Transactions on Robotics and Automation, 2001
- A solution to the simultaneous localization and map building (SLAM) problemIEEE Transactions on Robotics and Automation, 2001