Abstract
Abstract. The paper presents a flexible approach for the geometric calibration of a 2D infrared laser scanning range finder. It does not require spatial object data, thus avoiding the time-consuming determination of reference distances or coordinates with superior accuracy. The core contribution is the development of an integrated bundle adjustment, based on the flexible principle of a self-calibration. This method facilitates the precise definition of the geometry of the scanning device, including the estimation of range-measurement-specific correction parameters. The integrated calibration routine jointly adjusts distance and angular data from the laser scanning range finder as well as image data from a supporting DSLR camera, and automatically estimates optimum observation weights. The validation process carried out using a Hokuyo UTM-30LX-EW confirms the correctness of the proposed functional and stochastic contexts and allows detailed accuracy analyses. The level of accuracy of the observations is computed by variance component estimation. For the Hokuyo scanner, we obtained 0.2% of the measured distance in range measurement and 0.2 deg for the angle precision. The RMS error of a 3D coordinate after the calibration becomes 5 mm in lateral and 9 mm in depth direction. Particular challenges have arisen due to a very large elliptical laser beam cross-section of the scanning device used.
Highlights
Rogers III et al (2010) use compact laser scanning range finders (LSRF) for simultaneous mobile robot localization and mapping (SLAM) in an indoor office environment
Overall 100 convergent images, some of them rolled against the camera axis, ensure a stable network geometry
Even though probably not all LSRF effects are considered, the results show that the integration of LSRF correction parameters is better suited to model the geometric-physical reality of a LSRF measurement process
Summary
Rogers III et al (2010) use compact laser scanning range finders (LSRF) for simultaneous mobile robot localization and mapping (SLAM) in an indoor office environment. Whether for navigation or for mapping tasks, a calibration of the laser scanning system is reasonable to maximize data accuracy This contribution proposes a flexible method for LSRF system self-calibration. Lichti and Gordon (2004) use a probabilistic model to specify the magnitude of this unpredictable error to be equal to one-quarter of the laser beam diameter Target properties such as color, brightness and material may have a significant influence on LSRF measurements (Kneip et al, 2009). A vertical offset of the laser axis from the trunnion axis as well as cyclic distance errors are supposed to be not existent for a 2D single-layer time-of-flight LSRF (section 2). The further development for compact and light-weight single-layer 2D LSRF is the main core of this contribution
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