Cost effective mobile mapping system for color point cloud reconstruction

Cheng Wei Peng, Chen Chien Hsu*, Wei Yen Wang


研究成果: 雜誌貢獻期刊論文同行評審

6 引文 斯高帕斯(Scopus)


Survey-grade Lidar brands have commercialized Lidar-based mobile mapping systems (MMSs) for several years now. With this high-end equipment, the high-level accuracy quality of point clouds can be ensured, but unfortunately, their high cost has prevented practical implementation in autonomous driving from being affordable. As an attempt to solve this problem, we present a cost-effective MMS to generate an accurate 3D color point cloud for autonomous vehicles. Among the major processes for color point cloud reconstruction, we first synchronize the timestamps of each sensor. The calibration process between camera and Lidar is developed to obtain the translation and rotation matrices, based on which color attributes can be composed into the corresponding Lidar points. We also employ control points to adjust the point cloud for fine tuning the absolute position. To overcome the limitation of Global Navigation Satellite System/Inertial Measurement Unit (GNSS/IMU) positioning system, we utilize Normal Distribution Transform (NDT) localization to refine the trajectory to solve the multi-scan dispersion issue. Experimental results show that the color point cloud reconstructed by the proposed MMS has a position error in centimeter-level accuracy, meeting the requirement of high definition (HD) maps for autonomous driving usage.

頁(從 - 到)1-19
期刊Sensors (Switzerland)
出版狀態已發佈 - 2020 11月 2

ASJC Scopus subject areas

  • 分析化學
  • 資訊系統
  • 原子與分子物理與光學
  • 生物化學
  • 儀器
  • 電氣與電子工程


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