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Appearance-Based Place Recognition Using Whole-Image BRISK for Collaborative Multi-Robot Localization

Jung H. Oh, Gyuho Eoh, and Beom H. Lee
Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea

Abstract—This paper deals with the problem of recognizing places based on their appearance for collaborative mobile robot localization. A whole-image descriptor and BRISK are combined in order to extract information from images collected by multiple mobile robots. The bag-of-words method is then adopted to calculate similarity scores between obtained images, and this enables each robot to find other robots’ previously visited locations. Such detections make it possible to increase the precision of the actual pose estimates and achieve a precise collaborative localization. Experiments are performed to verify the effectiveness of the proposed method in outdoor environments.
 
Index Terms—place recognition, loop closures, BRISK, image descriptor, multi-robot, Simultaneous Localization and Mapping (SLAM)
Cite: Jung H. Oh, Gyuho Eoh, and Beom H. Lee, "Appearance-Based Place Recognition Using Whole-Image BRISK for Collaborative Multi-Robot Localization," International Journal of Mechanical Engineering and Robotics Research, Vol.4, No. 3, pp. 264-268, July 2015. DOI: 10.18178/ijmerr.4.3.264-268