Abstract
Abstract
Extrinsic Calibration between LiDAR and POS (position and orientation system) is a fundamental prerequisite for varieties of MLS (mobile laser scanner) applications. Due to the sparse structure of LiDAR data, the current calibration methods relying on common point feature matching are unreliable, and the low accuracy POS results make the extrinsic calibration of MLS system more challenging. In this paper, we propose an incremental estimation method of six degree of freedom extrinsic transformation of LiDAR and POS. Firstly, the POS-SLAM is used to accumulate LiDAR scans as online sub maps. Attitudes of the carrier are calculated by using GNSS/INS loose combination method of bidirectional adjustment, and scans are associated with sub map based on the time interpolation. Then, the extrinsic calibration parameters are estimated by optimizing corresponding points difference between SLAM and MLS coordinate frame. Finally, field tests have been conducted to the proposed method. RMS between the map by the calibrated MLS and by the static measurement is 0.57 cm. The results demonstrate that the accuracy and robustness of our calibration approach are sufficient for mapping requirement of MLS.
Funder
National Key R&D Program of China
Provincial key research and development program of Hubei
Subject
Applied Mathematics,Instrumentation,Engineering (miscellaneous)
Cited by
1 articles.
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1. Sensing Quality Driven Positioning and Orientation for LiDAR Sensors;2023 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT);2023-12-10