Integration of the Velodyne LiDAR Sensor and Pixhawk for Indoor 3D Mapping

Nurya Ramadhania, Mokhamad Nur Cahyadi*, Tahiyatul Asfihani, Hendy Fitrian Suhandri

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

The importance of indoor mapping has surged across various applications, encompassing human navigation, indoor exploration, and hazardous site mapping. With satellite positioning systems ineffective indoors, alternative navigational sensors and methods, such as inertial measurement units (IMU) and simultaneous localization and mapping algorithms (SLAM), have been harnessed to furnish precise indoor positioning for mapping endeavors. Leveraging LiDAR-based SLAM, which is sensitive to environmental textures and various pose configurations, addresses these challenges. In order to accomplish reliable and precise indoor 3D mapping, this study combines the Velodyne VLP-16 3D-LiDAR sensor with the Pixhawk Cube Orange, which has a 9 Degrees of Freedom (DOF) IMU sensor. The study uses the LIO-SAM (LiDAR Inertial Odometry and Simultaneous Localization and Mapping) technique, which integrates data from LiDAR and IMU to increase mapping precision. It is carried out at the BAAK Dr. Angka Building, Institut Teknologi Sepuluh Nopember, Surabaya. The experimental results reveal that the 3D indoor mapping exhibits commendable visualization and high geometric accuracy, meeting the LoD 3 criteria. Validation using a roll meter yielded a root mean square error (RMSE) of 0.3552 meters, indicating considerable accuracy. The accuracy was further validated by showing LiDAR point cloud errors ranging from 7.92% to 15.75%. Linear regression analysis confirmed a high correlation (R2 0.9954) between LiDAR point cloud measurements and manual measurements, substantiating the method's reliability. In order to accomplish reliable and precise indoor 3D mapping, this study combines the Velodyne VLP-16 3D-LiDAR sensor with the Pixhawk Cube Orange, which has a 9 Degrees of Freedom (DOF) IMU sensor. The study uses the LIO-SAM (LiDAR Inertial Odometry and Simultaneous Localization and Mapping) technique, which integrates data from LiDAR and IMU to increase mapping precision. It is carried out at the BAAK Dr. Angka Building, Institut Teknologi Sepuluh Nopember, Surabaya.

Original languageEnglish
Article number012025
JournalIOP Conference Series: Earth and Environmental Science
Volume1418
Issue number1
DOIs
Publication statusPublished - 2024
Event9th Geomatics International Conference 2024, GeoICON 2024 - Surabaya, Indonesia
Duration: 24 Jul 2024 → …

Keywords

  • Geometric Accuracy
  • LiDAR Velodyne
  • LiDAR-based SLAM
  • Pixhawk
  • indoor mapping

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