Development and calibration of KaRoLa, a compact, high-resolution 3D laser scanner

Pfotzer, L.; Oberlaender, Jan; Roennau, Arne; Dillmann, Ruediger

doi:10.1109/ssrr.2014.7017677

Cited by 11 publications

(3 citation statements)

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“…Since the manufacturing and assembly of the mechanical parts cannot be absolutely precise, mechanical error is unavoidable. In [10,[20][21][22][23][24][25][26][27][28][29][30][31], calibration methods of the mechanical error have been studied.…”

Section: Problem 12-for Categories 1 2 and 5: The Error Caused By The...mentioning

confidence: 99%

“…First, there is the problem of accuracy, primarily due to the error of the 2D LiDAR movement estimation. Specifically, this error may originate from the installation error between the 2D Li-DAR and the moving unit [10,[20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35], or it may originate from the inaccurate movement estimation of the moving unit [36][37][38][39][40][41].…”

Section: Introductionmentioning

confidence: 99%

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A Survey of Low-Cost 3D Laser Scanning Technology

Yuan

Liu

et al. 2021

Applied Sciences

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By moving a commercial 2D LiDAR, 3D maps of the environment can be built, based on the data of a 2D LiDAR and its movements. Compared to a commercial 3D LiDAR, a moving 2D LiDAR is more economical. A series of problems need to be solved in order for a moving 2D LiDAR to perform better, among them, improving accuracy and real-time performance. In order to solve these problems, estimating the movements of a 2D LiDAR, and identifying and removing moving objects in the environment, are issues that should be studied. More specifically, calibrating the installation error between the 2D LiDAR and the moving unit, the movement estimation of the moving unit, and identifying moving objects at low scanning frequencies, are involved. As actual applications are mostly dynamic, and in these applications, a moving 2D LiDAR moves between multiple moving objects, we believe that, for a moving 2D LiDAR, how to accurately construct 3D maps in dynamic environments will be an important future research topic. Moreover, how to deal with moving objects in a dynamic environment via a moving 2D LiDAR has not been solved by previous research.

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Section: Problem 12-for Categories 1 2 and 5: The Error Caused By The...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Survey of Low-Cost 3D Laser Scanning Technology

Yuan

Liu

et al. 2021

Applied Sciences

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“…For example, Alismail and Browning (Alismail and Browning, 2015) proposed a calibration of 2degree-of-freedom (DOF) rotation and 2-DOF translation with rolling motion based on the assumption of locally smooth surfaces, using a motor like mentioned above. Pfotzer et al (2014) presented a calibration method that can be run online by simply taking a full 360°scan of a reasonably large environment. In Oberlaender et al (2015) presented an approach using only a single scan of a target less environment recorded over a complete 360°rotation of the external motor that controls the motion of the 2D sensor.…”

Section: Introduction and Related Workmentioning

confidence: 99%

Calibration of rotating 2D LIDAR based on simple plane measurement

Gao

Huang

Yang

et al. 2019

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Purpose This paper aims to calibrate the mounted parameters between the LIDAR and the motor in a low-cost 3D LIDAR device. It proposes the model of the aimed 3D LIDAR device and analyzes the influence of all mounted parameters. The study aims to find a way more accurate and simple to calibrate those mounted parameters. Design/methodology/approach This method minimizes the coplanarity and area of the plane scanned to estimate the mounted parameters. Within the method, the authors build different cost function for rotation parameters and translation parameters; thus, the parameter estimation problem of 4-degree-of-freedom (DOF) is decoupled into 2-DOF estimation problem, achieving the calibration of these two types of parameters. Findings This paper proposes a calibration method for accurately estimating the mounted parameters between a 2D LIDAR and rotating platform, which realizes the estimation of 2-DOF rotation parameters and 2-DOF translation parameters without additional hardware. Originality/value Unlike previous plane-based calibration techniques, the main advantage of the proposed method is that the algorithm can estimate the most and more accurate parameters with no more hardware.

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