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Automatic Calibration of Spinning Actuated Lidar Internal Parameters
Author(s) -
Alismail Hatem,
Browning Brett
Publication year - 2015
Publication title -
journal of field robotics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.152
H-Index - 96
eISSN - 1556-4967
pISSN - 1556-4959
DOI - 10.1002/rob.21543
Subject(s) - lidar , calibration , spinning , point cloud , computer science , rotation (mathematics) , remote sensing , artificial intelligence , computer vision , engineering , geology , physics , mechanical engineering , quantum mechanics
Actuated lidar, where a scanning lidar is combined with an actuation mechanism to scan a three‐dimensional volume rather than a single line, has been used heavily in a wide variety of field robotics applications. Common examples of actuated lidar include spinning/rolling and nodding/pitching configurations. Due to the construction of actuated lidar, the center of rotation of the lidar mirror may not coincide with the center of rotation of the actuation mechanism. To triangulate a precise point cloud representation of the environment, the centers of rotation must be brought into alignment using a suitable calibration procedure. We refer to this problem as estimating the internal parameters of actuated lidar. In this work, we focus on spinning/rolling lidar and present a fully automated algorithm for calibration using generic scenes without the need for specialized calibration targets. The algorithm is evaluated on a range of real and synthetic data and is shown to be robust, accurate, and have a large basin of convergence.