Abstract
This article aims to solve the problem of ghost trail effect left by dynamic objects and improve the accuracy of localization and mapping purity. Based on the tightly-coupled LiDAR inertial odometry via smoothing and mapping (LIO-SAM), a real-time dynamic region removal method is proposed to challenge the real high dynamic environment. A vertical voxel height descriptor is presented to accurately discriminate dynamic and static points. Inertial measurement unit (IMU) pre-integration is used for initial pose estimation to preferentially remove dynamic objects. A weighted optimization strategy is designed to improve the accuracy of pose estimation. The proposed algorithms are tested on self-collected dataset and the public UrbanLoco dataset, and achieve good real-time performance, mitigating the effect of dynamic objects in various scenes. The results verify that the DRR-LIO can well remove dynamic objects and improve localization accuracy.
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