사이드 스캔 소나 기반 Pose-graph SLAM Side Scan Sonar based Pose-graph SLAM

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Side scanning sonar (SSS) provides valuable information for robot navigation. However using the side scanning sonar images in the navigation was not fully studied. In this paper, we use range data, and side scanning sonar images from UnderWater Simulator (UWSim) and propose measurement models in a feature based simultaneous localization and mapping (SLAM) framework. The range data is obtained by echosounder and sidescanning sonar images from side scan sonar module for UWSim. For the feature, we used the A-KAZE feature for the SSS image matching and adjusting the relative robot pose by SSS bundle adjustment (BA) with Ceres solver. We use BA for the loop closure constraint of pose-graph SLAM. We used the Incremental Smoothing and Mapping (iSAM) to optimize the graph. The optimized trajectory was compared against the dead reckoning (DR).
Publisher
한국로봇학회
Issue Date
2017-12
Language
Korean
Keywords

Side Scan Sonar; Feature Extractor; Image Matching; UWSim; Underwater Navigation; Pose-graph SLAM

Citation

로봇학회 논문지, v.12, no.4, pp.385 - 394

ISSN
1975-6291
DOI
10.7746/jkros.2017.12.4.385
URI
http://hdl.handle.net/10203/228578
Appears in Collection
CE-Journal Papers(저널논문)
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