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Adaptive planar vision marker composed of LED arrays for sensing under low visibility
Kim, Kyukwang,Hyun, Jieum,Myung, Hyun Techno-Press 2018 Advances in robotics research Vol.2 No.2
In image processing and robotic applications, two-dimensional (2D) black and white patterned planar markers are widely used. However, these markers are not detectable in low visibility environment and they are not changeable. This research proposes an active and adaptive marker node, which displays 2D marker patterns using light emitting diode (LED) arrays for easier recognition in the foggy or turbid underwater environments. Because each node is made to blink at a different frequency, active LED marker nodes were distinguishable from each other from a long distance without increasing the size of the marker. We expect that the proposed system can be used in various harsh conditions where the conventional marker systems are not applicable because of low visibility issues. The proposed system is still compatible with the conventional marker as the displayed patterns are identical.
RGB-D and Magnetic Sequence-based Graph SLAM with Kidnap Recovery
Hyungjin Kim,Seungwon Song,Jieum Hyun,Soon Hyuk Hong,Hyun Myung 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10
This paper introduces graph structure-based simultaneous localization and mapping (SLAM) using RGB-D and magnetic sensors. We also propose kidnap recovery with graph SLAM structure. The RGB-D sensor can measure the distance value of the corresponding image pixel and magnetic sensor can measure magnetic field distortion in an indoor environment. Since these two sensors have different characteristics, they have different strengths when performing SLAM. RGB-D sensor-based SLAM is suitable for complex 3D environments, and magnetic sensor-based SLAM provides better performance in feature-poor environments such as corridors. Thus, this paper introduces a robust SLAM system in indoor environment by taking advantages of both sensor characteristics. The proposed algorithm has been tested to verify the superiority of algorithms in indoor environment and kidnapping situations.