Abstract

A high-precision mapping is one of the essential requirements for safe autonomous driving because it is directly connected with the accuracy and safety of autonomous driving. Due to the development of 3D light detection and ranging (LiDAR) sensor technology, LiDAR is playing a key role to create the precise maps. Although many open-source-based LiDAR simultaneous localization and mapping (SLAM) algorithms have been developed, their accuracy in actual experiments is often not proven. To handle this issue, our paper aims to provide background materials for autonomous robots and experimental validations of open-source-based LiDAR SLAM. In the experiments, the comparison results with four state-of-the-art LiDAR mapping algorithms are described including LiDAR odometry and mapping(LOAM) and LiDAR inertial odometry mapping.

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