The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Intensity and Ambient Enhanced Lidar-Inertial SLAM for Unstructured Construction Environment

비정형의 건설환경 매핑을 위한 레이저 반사광 강도와 주변광을 활용한 향상된 라이다-관성 슬램

  • Jung, Minwoo (Dept. of Civil and Environmental Engineering, KAIST) ;
  • Jung, Sangwoo (Dept. of Civil and Environmental Engineering, KAIST) ;
  • Jang, Hyesu (Dept. of Civil and Environmental Engineering, KAIST) ;
  • Kim, Ayoung (Dept. of Civil and Environmental Engineering, KAIST)
  • Received : 2021.04.27
  • Accepted : 2021.06.06
  • Published : 2021.08.31
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Abstract

Construction monitoring is one of the key modules in smart construction. Unlike structured urban environment, construction site mapping is challenging due to the characteristics of an unstructured environment. For example, irregular feature points and matching prohibit creating a map for management. To tackle this issue, we propose a system for data acquisition in unstructured environment and a framework for Intensity and Ambient Enhanced Lidar Inertial Odometry via Smoothing and Mapping, IA-LIO-SAM, that achieves highly accurate robot trajectories and mapping. IA-LIO-SAM utilizes a factor graph same as Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping (LIO-SAM). Enhancing the existing LIO-SAM, IA-LIO-SAM leverages point's intensity and ambient value to remove unnecessary feature points. These additional values also perform as a new factor of the K-Nearest Neighbor algorithm (KNN), allowing accurate comparisons between stored points and scanned points. The performance was verified in three different environments and compared with LIO-SAM.

Keywords

Acknowledgement

This work is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (National Research for Smart Construction Technology: Grant 21SMIP-A158708-02)

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