EVALUATION OF LIDAR ODOMETRY AND MAPPING BASED ON REFERENCE LASER SCANNING

Q2 Social Sciences The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences Pub Date : 2023-10-19 DOI:10.5194/isprs-archives-xlviii-1-w3-2023-79-2023

J. Koszyk, P. Łabędź, K. Grzelka, A. Jasińska, K. Pargieła, A. Malczewska, K. Strząbała, M. Michalczak, Ł. Ambroziński

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Abstract

Abstract. Simultaneous localization and mapping (SLAM) is essential for the robot to operate in an unknown, vast environment. LiDAR-based SLAM can be utilizable in environments where other sensors cannot deliver reliable measurements. Providing accurate map results requires particular attention due to deviations originating from the device. This study is aimed to assess LiDAR-based mapping quality in a vast environment. The measurements are conducted on a mobile platform. Accuracy of the map collected with the LeGO-LOAM method was performed by making a comparison to a map gathered with geodetic scanning using ICP. The results provided 60% of fitted points in a distance lower than 5 cm and 80% in a distance lower than 10 cm. The findings prove the mileage of the map created with this method for other tasks, including autonomous driving and semantic segmentation.

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基于参考激光扫描的激光雷达测程和测绘评估

摘要同时定位和测绘(SLAM)是机器人在未知的广阔环境中运行的必要条件。基于激光雷达的SLAM可用于其他传感器无法提供可靠测量的环境。由于设备产生的偏差，提供准确的地图结果需要特别注意。本研究旨在评估广阔环境下基于lidar的制图质量。测量是在移动平台上进行的。通过将LeGO-LOAM方法收集的地图与使用ICP进行大地测量扫描收集的地图进行比较，来确定地图的准确性。结果显示，60%的拟合点的距离小于5厘米，80%的拟合点的距离小于10厘米。研究结果证明，用这种方法创建的地图的里程可以用于其他任务，包括自动驾驶和语义分割。

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