Monocular cameras and planar lidar sensors are complementary. While monocular visual odometry (VO) is a relatively low-drift method for measuring platform egomotion, it suffers from a scale ambiguity. A planar lidar scanner, in contrast, is able to provide precise distance information with known scale. In combination, a monocular camera-2D lidar pair can be used as a performance 3D scanner, at a much lower cost than existing 3D lidar units. However, for accurate scan acquisition, the two sensors must be spatially and temporally calibrated. In this paper, we extend recent work on a calibration technique based on Rényi’s quadratic entropy (RQE) to the unified spatiotemporal calibration of monocular cameras and 2D lidars. We present simulation results indicating that calibration errors of less than 5 mm, 0.1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^\circ $$\end{document}, and 0.15 ms in translation, rotation, and time delay, respectively, are readily achievable. Using real-world data, in the absence of reliable ground truth, we demonstrate high repeatability given sufficient platform motion. Unlike existing techniques, we are able to calibrate in arbitrary, target-free environments and without the need for overlapping sensor fields of view.


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    Title :

    Unified Spatiotemporal Calibration of Monocular Cameras and Planar Lidars


    Additional title:

    Springer Proceedings in Advanced Robotics


    Contributors:

    Conference:

    International Symposium on Experimental Robotics ; 2018 ; Buenos Aires, Argentina November 05, 2018 - November 08, 2018



    Publication date :

    2020-01-23


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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