Cheong, Howon Kim, Euntai Park, Sung-Kee 2024-01-19T18:34:31Z 2024-01-19T18:34:31Z 2021-09-05 2019-11-15 1530-437X https://pubs.kist.re.kr/handle/201004/119318 This paper suggests a new landmark descriptor for indoor mobile robot navigation with sensor fusion and a global localization method using it. In previous research on robot pose estimation, various landmarks such as geometric features, visual local-invariant features, or objects are utilized. However, in real-world situations, there is a possibility that distinctive landmarks are insufficient or there are many similar landmarks repeated in indoor environment, which makes accurate pose estimation difficult. In this work, we suggest a new landmark descriptor, called depth-guided photometric edge descriptor (DPED), which is composed of superpixels and approximated 3D depth information of photometric vertical edge. With this descriptor, we propose a global localization method based on coarse-to-fine strategy. In the coarse step, candidate nodes are found by place recognition using our pairwise constraint-based spectral matching technique, and the robot pose is estimated with a probabilistic scan matching in the fine step. The experimental results show that our method successfully estimates the robot pose in the real-world tests even when there is a lack of distinctive features and objects. English IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC VISION Indoor Global Localization Using Depth-Guided Photometric Edge Descriptor for Mobile Robot Navigation Article 10.1109/JSEN.2019.2932131 1 IEEE SENSORS JOURNAL, v.19, no.22, pp.10837 - 10847 IEEE SENSORS JOURNAL 19 22 10837 10847 scie scopus 000503399200078 2-s2.0-85073880260 Engineering, Electrical & Electronic Instruments & Instrumentation Physics, Applied Engineering Instruments & Instrumentation Physics Article VISION Mobile robot global localization sensor fusion spectral matching