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Need help: lidar vs. stereo cameras on the KITTI benchmark for odometry/SLAM

Discussion in 'Autonomous Vehicles' started by strangecosmos, Jul 30, 2018.

  1. strangecosmos

    strangecosmos Non-Member

    Joined:
    May 10, 2017
    Messages:
    679
    Location:
    Koopa Kingdom
    I need help interpreting some data. Here is the leaderboard for the performance of different odometry/SLAM approaches, benchmarked against the KITTI Vision dataset:

    [​IMG]

    The top approach, V-LOAM, uses lidar. The fourth best approach, SOFT2, uses stereo camera images, and no lidar data. The rotation error is the same for SOFT2 and V-LOAM, and the translation error for SOFT2 is 0.05% higher.

    On the face of it, this would seem to imply that the current best stereo camera-based odometry/SLAM method is pretty close in accuracy to the current beat lidar-based method. Am I wrong? Is is a 0.05% difference actually huge? Am I otherwise misunderstanding or misinterpreting what’s going on here? Any help anyone can provide would be much appreciated. Thanks.
     

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