Calibration of Large Scale Coordinate Measuring System Based on Scanning Laser Plane

2012 ◽  
Vol 503-504 ◽  
pp. 1270-1275 ◽  
Author(s):  
Da Bao Lao ◽  
Wei Hu Zhou ◽  
Zi Li Zhang ◽  
Xue You Yang ◽  
Ji Gui Zhu
Keyword(s):  
Large Scale ◽  
Calibration Method ◽  
Measurement Model ◽  
Bundle Adjustment ◽  
Measuring System ◽  
Coordinate Frame ◽  
Coordinate Measurement ◽  
Global Calibration ◽  
Planar Laser ◽  
Measuring Network

To overcome the disadvantages of existing large-scale coordinate measurement systems about low level of automation and poor parallelism, this paper introduces a novel system which characters multi-sensor measuring network, while a single sensor measures angle via a couple of non-parallel planar laser beams rotating around a fixed shaft. The novel method for measuring angle improves automation in large-scale coordinate measurement. Furthermore, measuring network assures that measurement accuracy keeps to the same level even when the measuring range is enlarged. Measurement model and calibration are the key technologies of the system. They are the main sources of measuring errors. Therefore, to minimize the error, a practical global calibration method for the multi-sensor network system is proposed, with constructing a precise mathematical model. In this model, the parameters of the system are divided to inner and outer parts. While the inner parameters are obtained by aided instrument, the outer which means transform parameters between different sensors are figured out in spot calibration. Finally, the objective function based on transform coefficients between different sensor coordinate systems is defined and the outer parameters are optimized by bundle adjustment method. Thus, the whole system can finish global calibration by one time，and no medi-coordinate-frame is needed．Therewith，transformation time of coordinate frame decreases and calibration process is facilitated. Finally，measurement experiments are conducted with root mean square(RMS) error of not more than 0.1 mm.

An Improved Calibration Method for Optical 3D Measuring System Using Cross Target Based on Bundle Adjustment Algorithm

2010 ◽  
Vol 97-101 ◽  
pp. 4237-4242 ◽  
Author(s):  
Zhen Zhong Xiao ◽  
Jin Liang ◽  
De Hong Yu ◽  
Zheng Zong Tang
Keyword(s):  
Large Scale ◽  
Coordinate Measuring Machine ◽  
Calibration Method ◽  
Bundle Adjustment ◽  
Measuring System ◽  
Measurement Systems ◽  
Large Scale Field ◽  
Orientation Method ◽  
Measuring Machine ◽  
Direct Linear Transform

This paper presents an accurate calibration method of binocular 3D measurement systems for industrial on-site inspection, which uses a cross target with ring coded points. The cross target can be used to calibrate large-scale field-of-view stereo measurement systems and obtain higher measurement precision conveniently. The world coordinates of these ring coded points are not required. The calibration initial value is computed by using the relative orientation method and the Direct Linear Transform (DLT) method of photogrammetry. The bundle adjustment algorithm is used to optimize the calibration parameters as well as the 3D coordinates of the ring coded points. Experiment results show that the RMS error of the reprojection in our method is less than 0.05 pixels and the measurement error is 0.011 mm compared with the Coordinate Measuring Machine (CMM).

scholarly journals Global Measurement Method for Large-Scale Components Based on a Multiple Field of View Combination

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Yang Zhang ◽  
Wei Liu ◽  
Zhiguang Lan ◽  
Zhiyuan Zhang ◽  
Fan Ye ◽  
...  
Keyword(s):  
Measurement System ◽  
Measurement Method ◽  
Large Scale ◽  
Vision System ◽  
Calibration Method ◽  
Field Of View ◽  
Surface Measurement ◽  
Global Calibration ◽  
Multiple Field ◽  
Measurement Efficiency

Considering the limited measurement range of a machine vision method for the three-dimensional (3D) surface measurement of large-scale components, a noncontact and flexible global measurement method combining a multiple field of view (FOV) is proposed in this paper. The measurement system consists of two theodolites and a binocular vision system with a transfer mark. The process of multiple FOV combinations is described, and a new global calibration method is proposed to solve the coordinate system unification issue of different instruments in the measurement system. In addition, a high-precision image acquisition method, which is based on laser stripe scanning and centre line extraction, is discussed to guarantee the measurement efficiency. With the measured 3D data, surface reconstruction of large-scale components is accomplished by data integration. Experiments are also conducted to verify the precision and effectiveness of the global measurement method.

A Laser Tracking-Vision Guiding Measurement System for Large-Scale Parts Assembly

2013 ◽  
Vol 718-720 ◽  
pp. 868-874 ◽  
Author(s):  
Wen Sun
Keyword(s):  
Measurement System ◽  
Large Scale ◽  
Automatic Measurement ◽  
Calibration Method ◽  
Laser Tracking ◽  
Measurement Systems ◽  
Global Calibration ◽  
Real Time Tracking ◽  
Low Efficiency ◽  
High Degree

To address the problems of low efficiency, high cost and low automatic level existing in traditional laser tracking measurement systems, a laser tracking-vision guiding measurement system for large-scale parts assembly is introduced in this paper. The system is composed of mono-camera and a laser tracker, can fulfill real-time tracking and automatic measurement throughout the whole assembly process. A global calibration method based on public planes and a method for finding the 3D positions of the target reflectors based on monocular vision measuring are expounded. Mathematical model is established, measurement system is built, and the experiment is accomplished. The experiment result indicates that the proposed system features relative high degree of automation and high measuring speed, has future in practical application.

scholarly journals Flexible and Accurate Calibration Method for Non-Overlapping Vision Sensors Based on Distance and Reprojection Constraints

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4623 ◽  
Author(s):  
Tao Jiang ◽  
Xu Chen ◽  
Qiang Chen ◽  
Zhe Jiang
Keyword(s):  
Calibration Method ◽  
Bundle Adjustment ◽  
Experimental Results ◽  
Laser Tracker ◽  
Distance Error ◽  
Global Calibration ◽  
Vision Sensors ◽  
Extrinsic Parameters ◽  
Calibration Pattern

This paper addresses the problem of flexible and accurate global calibration for multiple non-overlapping vision sensors in a confined workspace. Instead of using an auxiliary calibration pattern, the proposed method uses one laser tracker and only its accessory target sphere to obtain all the 3D calibration points and then accomplish the initial estimation of pose between the vision sensors. Then, the 3D calibration points and the extrinsic parameters between vision sensors are further optimized via the bundle adjustment algorithm based on the distance and reprojection constraints. Experiments were conducted to validate the performance and the experimental results demonstrate that the distance error can be decreased from 3.5 mm to 0.8 mm after introducing the distance and reprojection constraints.

Optimization of calibration method for scanning planar laser coordinate measurement system

2011 ◽  
Vol 19 (4) ◽  
pp. 870-877 ◽  
Author(s):  
劳达宝 LAO Da-bao ◽  
杨学友 YANG Xue-you ◽  
邾继贵 ZHU Ji-gui ◽  
叶声华 YE Sheng-hua
Keyword(s):  
Measurement System ◽  
Calibration Method ◽  
Coordinate Measurement ◽  
Planar Laser

scholarly journals UCalMiCeL – UNIFIED INTRINSIC AND EXTRINSIC CALIBRATION OF A MULTI-CAMERA-SYSTEM AND A LASERSCANNER

2017 ◽  
Vol IV-2/W3 ◽  
pp. 17-24 ◽  
Author(s):  
M. Hillemann ◽  
B. Jutzi
Keyword(s):  
Large Scale ◽  
Calibration Method ◽  
Bundle Adjustment ◽  
Sensor System ◽  
Small Scale ◽  
Camera System ◽  
Extrinsic Calibration ◽  
Camera Systems ◽  
The Individual ◽  
Calibration Approach

Unmanned Aerial Vehicle (UAV) with adequate sensors enable new applications in the scope between expensive, large-scale, aircraftcarried remote sensing and time-consuming, small-scale, terrestrial surveyings. To perform these applications, cameras and laserscanners are a good sensor combination, due to their complementary properties. To exploit this sensor combination the intrinsics and relative poses of the individual cameras and the relative poses of the cameras and the laserscanners have to be known. In this manuscript, we present a calibration methodology for the <i>Unified Intrinsic and Extrinsic Calibration of a Multi-Camera-System and a Laserscanner (UCalMiCeL)</i>. The innovation of this methodology, which is an extension to the calibration of a single camera to a line laserscanner, is an unifying bundle adjustment step to ensure an optimal calibration of the entire sensor system. We use generic camera models, including pinhole, omnidirectional and fisheye cameras. For our approach, the laserscanner and each camera have to share a joint field of view, whereas the fields of view of the individual cameras may be disjoint. The calibration approach is tested with a sensor system consisting of two fisheye cameras and a line laserscanner with a range measuring accuracy of 30&amp;thinsp;<i>mm</i>. We evaluate the estimated relative poses between the cameras quantitatively by using an additional calibration approach for Multi-Camera-Systems based on control points which are accurately measured by a motion capture system. In the experiments, our novel calibration method achieves a relative pose estimation with a deviation below 1.8&amp;deg; and 6.4&amp;thinsp;<i>mm</i>.

scholarly journals A High-Precision Registration Technology Based on Bundle Adjustment in Structured Light Scanning System

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Jianying Yuan ◽  
Qiong Wang ◽  
Xiaoliang Jiang ◽  
Bailin Li
Keyword(s):  
High Precision ◽  
Large Scale ◽  
Structured Light ◽  
Bundle Adjustment ◽  
Scanning System ◽  
Control Points ◽  
Registration Method ◽  
Global Control ◽  
3D Data ◽  
Structured Light Scanning

The multiview 3D data registration precision will decrease with the increasing number of registrations when measuring a large scale object using structured light scanning. In this paper, we propose a high-precision registration method based on multiple view geometry theory in order to solve this problem. First, a multiview network is constructed during the scanning process. The bundle adjustment method from digital close range photogrammetry is used to optimize the multiview network to obtain high-precision global control points. After that, the 3D data under each local coordinate of each scan are registered with the global control points. The method overcomes the error accumulation in the traditional registration process and reduces the time consumption of the following 3D data global optimization. The multiview 3D scan registration precision and efficiency are increased. Experiments verify the effectiveness of the proposed algorithm.

scholarly journals Optimization-Based Online Initialization and Calibration of Monocular Visual-Inertial Odometry Considering Spatial-Temporal Constraints

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2673
Author(s):  
Weibo Huang ◽  
Weiwei Wan ◽  
Hong Liu
Keyword(s):  
Measurement Data ◽  
Calibration Method ◽  
Bundle Adjustment ◽  
Measurement Unit ◽  
Temporal Parameters ◽  
Work Routine ◽  
Initial States ◽  
Time Offset ◽  
Public Datasets ◽  
Metric Scale

The online system state initialization and simultaneous spatial-temporal calibration are critical for monocular Visual-Inertial Odometry (VIO) since these parameters are either not well provided or even unknown. Although impressive performance has been achieved, most of the existing methods are designed for filter-based VIOs. For the optimization-based VIOs, there is not much online spatial-temporal calibration method in the literature. In this paper, we propose an optimization-based online initialization and spatial-temporal calibration method for VIO. The method does not need any prior knowledge about spatial and temporal configurations. It estimates the initial states of metric-scale, velocity, gravity, Inertial Measurement Unit (IMU) biases, and calibrates the coordinate transformation and time offsets between the camera and IMU sensors. The work routine of the method is as follows. First, it uses a time offset model and two short-term motion interpolation algorithms to align and interpolate the camera and IMU measurement data. Then, the aligned and interpolated results are sent to an incremental estimator to estimate the initial states and the spatial–temporal parameters. After that, a bundle adjustment is additionally included to improve the accuracy of the estimated results. Experiments using both synthetic and public datasets are performed to examine the performance of the proposed method. The results show that both the initial states and the spatial-temporal parameters can be well estimated. The method outperforms other contemporary methods used for comparison.

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