안드로이드 기반 테더드 타입 AR 글래스의 공간 인식을 위한 ORB-SLAM 기반 SLAM프레임워크 설계

ORB-SLAM based SLAM Framework for the Spatial Recognition using Android Oriented Tethered Type AR Glasses

  • 김도훈 (한국전자기술연구원 VR/AR 연구센터) ;
  • 국중진 (상명대학교 정보보안공학과)
  • Do-hoon Kim (VR/AR Research Center, Korea Electronics Technology Institute) ;
  • Joongjin Kook (Dept. of Information Security Engineering, Sangmyung University )
  • 투고 : 2023.01.26
  • 심사 : 2023.03.20
  • 발행 : 2023.03.31

초록

In this paper, we proposed a software framework structure to apply ORB-SLAM, the most representative of SLAM algorithms, so that map creation and location estimation technology can be applied through tethered AR glasses. Since tethered AR glasses perform only the role of an input/output device, the processing of camera and sensor data and the generation of images to be displayed through the optical display module must be performed through the host. At this time, an Android-based mobile device is adopted as the host. Therefore, the major libraries required for the implementation of AR contents for AR glasses were hierarchically organized, and spatial recognition and location estimation functions using SLAM were verified.

키워드

과제정보

이 연구는 2023년도 산업통상자원부 및 산업기술평가관리원(KEIT) 연구비 지원에 의한 연구임('20016882').

참고문헌

  1. INNOPOLIS , "SLAM Market", Retrieved Sep 18, 2021, from http://www.innopolis.or.kr, (May, 2020).
  2. SAMSUNG SDS, "[Direction and Implications of the Augmented Reality Technology Development] Part 2 Augmented Reality in Industrial Fields", Retrieved Sep 19, 2021, from https://www.samsungsds.com/kr/insights/augmented_reality_2.html (April 8, 2020).
  3. Changhyun Lee, Youngseop Kim, Yeonmin Kim, Inho Park, JaeHak Choi, Yonghwan Lee, Woori Han, "Study on the Content Development of Mobile AR_HMD through a Real Time 360 Image Processing," Journal of the Semiconductor & Display Technology, Vol. 15, Issue 2, pp. 66-69, 2016.
  4. Woo ri Han, Young-Seop Kim, Yong-Hwan Lee, "Multi-Object Tracking Based on Keypoints Using Homography in Mobile Environments," Journal of the Semiconductor & Display Technology, Vol. 14, Issue 3, pp. 67-72, 2015.
  5. Woo ri Han, Young-Seop Kim, Yong-Hwan Lee, "Multi-Object Tracking based on Reliability Assessment of Learning in Mobile Environment," Journal of the Semiconductor & Display Technology, Vol. 14, Issue 3, pp. 73-77, 2015.
  6. MAXST, "Where can Visual SLAM be used?", Retrieved Sep 19, 2021, from https://medium.com/maxst/where-can-visual-slam-be-used-b94876d161c6, (Oct 7, 2019).
  7. Raul Mur-Artal, Juan D.Tardos, "ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras," IEEE Transactions and Robotics, Vol.33, No. 5, pp. 1255-1262, 2017 https://doi.org/10.1109/TRO.2017.2705103
  8. Carlos Campos, Richard Elvira, Juan J. Gomez Rodriguez, Jose M.M. Montiel and Juan D. Tardos, "ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM," IEEE Transactions and Robotics, 2021
  9. RGB-D Benchmark Dataset, Technical University of Munich, https://vision.in.tum.de/data/datasets/rgbd-dataset