publication . Conference object . Preprint . 2018

IMLS-SLAM: scan-to-model matching based on 3D data

Jean-Emmanuel Deschaud;
Open Access English
  • Published: 22 May 2018
  • Publisher: HAL CCSD
  • Country: France
International audience; The Simultaneous Localization And Mapping (SLAM) problem has been well studied in the robotics community, especially using mono, stereo cameras or depth sensors. 3D depth sensors, such as Velodyne LiDAR, have proved in the last 10 years to be very useful to perceive the environment in autonomous driving, but few methods exist that directly use these 3D data for odometry. We present a new low-drift SLAM algorithm based only on 3D LiDAR data. Our method relies on a scan-to-model matching framework. We first have a specific sampling strategy based on the LiDAR scans. We then define our model as the previous localized LiDAR sweeps and use the...
Persistent Identifiers
free text keywords: [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], Computer Science - Robotics, Robotics, Computer vision, Artificial intelligence, business.industry, business, Moving least squares, Simultaneous localization and mapping, Lidar, Odometry, Observability, Stereo cameras, Sampling (statistics), Computer science
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