Calibration method of extrinsic parameters for non-orthogonal shaft laser theodolite measurement system

2021 ◽  
Author(s):  
Fengjin Miao ◽  
Bin Wu ◽  
Zefeng Sun ◽  
CongCong Peng
Keyword(s):  
Measurement System ◽  
Calibration Method ◽  
Extrinsic Parameters

The Calibration of Binocular Stereo Measurement System Based on a Coded Model

2013 ◽  
Vol 397-400 ◽  
pp. 1695-1699
Author(s):  
Hong Ming Chen ◽  
Hui Zhang
Keyword(s):  
Measurement System ◽  
Standard Error ◽  
Calibration Method ◽  
Bundle Adjustment ◽  
Target Point ◽  
Point Sets ◽  
Extrinsic Parameters ◽  
Binocular Stereo ◽  
Camera Coordinate System ◽  
Sparse Bundle Adjustment

A calibration method of binocular stereo measurement system is proposed based on a coded model. Target points are designed to be with the unique IDs which make the match of two pictures and the match of image points and 3D points reliable and stable. The intrinsic parameters of the two cameras are calculated precisely and the 3D target point sets are reconstructed in each camera coordinate system respectively by using the multiple view geometry constraint and a generic sparse bundle adjustment. Then the extrinsic parameters are calculated by using the rigid transform of the two 3D point sets. The accuracy of the re-projection results is 0.037 pixel of standard error.

scholarly journals A Convenient Calibration Method for LRF-Camera Combination Systems Based on a Checkerboard

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1315 ◽  
Author(s):  
Zhuang Zhang ◽  
Rujin Zhao ◽  
Enhai Liu ◽  
Kun Yan ◽  
Yuebo Ma
Keyword(s):  
Cost Function ◽  
High Precision ◽  
Measurement System ◽  
Calibration Method ◽  
Simulation Experiments ◽  
Extrinsic Parameters ◽  
Spatial Coordinates ◽  
Calibration Accuracy ◽  
Camera Parameters ◽  
2D And 3D

In this paper, a simple and easy high-precision calibration method is proposed for the LRF-camera combined measurement system which is widely used at present. This method can be applied not only to mainstream 2D and 3D LRF-cameras, but also to calibrate newly developed 1D LRF-camera combined systems. It only needs a calibration board to record at least three sets of data. First, the camera parameters and distortion coefficients are decoupled by the distortion center. Then, the spatial coordinates of laser spots are solved using line and plane constraints, and the estimation of LRF-camera extrinsic parameters is realized. In addition, we establish a cost function for optimizing the system. Finally, the calibration accuracy and characteristics of the method are analyzed through simulation experiments, and the validity of the method is verified through the calibration of a real system.

scholarly journals Extrinsic Parameters Calibration Method of Cameras with Non-Overlapping Fields of View in Airborne Remote Sensing

2018 ◽  
Vol 10 (8) ◽  
pp. 1298 ◽  
Author(s):  
Lei Yin ◽  
Xiangjun Wang ◽  
Yubo Ni ◽  
Kai Zhou ◽  
Jilong Zhang
Keyword(s):  
Remote Sensing ◽  
Camera Calibration ◽  
Calibration Method ◽  
Optimization Method ◽  
Airborne Remote Sensing ◽  
Camera System ◽  
Translation Error ◽  
Camera Systems ◽  
Calibration Methods ◽  
Extrinsic Parameters

Multi-camera systems are widely used in the fields of airborne remote sensing and unmanned aerial vehicle imaging. The measurement precision of these systems depends on the accuracy of the extrinsic parameters. Therefore, it is important to accurately calibrate the extrinsic parameters between the onboard cameras. Unlike conventional multi-camera calibration methods with a common field of view (FOV), multi-camera calibration without overlapping FOVs has certain difficulties. In this paper, we propose a calibration method for a multi-camera system without common FOVs, which is used on aero photogrammetry. First, the extrinsic parameters of any two cameras in a multi-camera system is calibrated, and the extrinsic matrix is optimized by the re-projection error. Then, the extrinsic parameters of each camera are unified to the system reference coordinate system by using the global optimization method. A simulation experiment and a physical verification experiment are designed for the theoretical arithmetic. The experimental results show that this method is operable. The rotation error angle of the camera’s extrinsic parameters is less than 0.001rad and the translation error is less than 0.08 mm.

scholarly journals Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4643
Author(s):  
Sang Jun Lee ◽  
Jeawoo Lee ◽  
Wonju Lee ◽  
Cheolhun Jang
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Image Features ◽  
Intelligent Vehicles ◽  
Point Problem ◽  
Reconstruction Method ◽  
Calibration Methods ◽  
The World ◽  
Extrinsic Parameters ◽  
Automatic Camera Calibration

In intelligent vehicles, extrinsic camera calibration is preferable to be conducted on a regular basis to deal with unpredictable mechanical changes or variations on weight load distribution. Specifically, high-precision extrinsic parameters between the camera coordinate and the world coordinate are essential to implement high-level functions in intelligent vehicles such as distance estimation and lane departure warning. However, conventional calibration methods, which solve a Perspective-n-Point problem, require laborious work to measure the positions of 3D points in the world coordinate. To reduce this inconvenience, this paper proposes an automatic camera calibration method based on 3D reconstruction. The main contribution of this paper is a novel reconstruction method to recover 3D points on planes perpendicular to the ground. The proposed method jointly optimizes reprojection errors of image features projected from multiple planar surfaces, and finally, it significantly reduces errors in camera extrinsic parameters. Experiments were conducted in synthetic simulation and real calibration environments to demonstrate the effectiveness of the proposed method.

A Self-Calibration Method for Robotic Measurement System

1999 ◽  
Author(s):  
Chunhe Gong ◽  
Jingxia Yuan ◽  
Jun Ni
Keyword(s):  
Coordinate System ◽  
Measurement System ◽  
Calibration Method ◽  
Position Measurement ◽  
Robot Calibration ◽  
Robot System ◽  
Self Calibration ◽  
World Coordinate System ◽  
Robot Accuracy ◽  
Calibration Methods

Abstract Robot calibration plays an increasingly important role in manufacturing. For robot calibration on the manufacturing floor, it is desirable that the calibration technique be easy and convenient to implement. This paper presents a new self-calibration method to calibrate and compensate for robot system kinematic errors. Compared with the traditional calibration methods, this calibration method has several unique features. First, it is not necessary to apply an external measurement system to measure the robot end-effector position for the purpose of kinematic identification since the robot measurement system has a sensor as its integral part. Second, this self-calibration is based on distance measurement rather than absolute position measurement for kinematic identification; therefore the calibration of the transformation from the world coordinate system to the robot base coordinate system, known as base calibration, is not necessary. These features not only greatly facilitate the robot system calibration but also shorten the error propagation chain, therefore, increase the accuracy of parameter estimation. An integrated calibration system is designed to validate the effectiveness of this calibration method. Experimental results show that after calibration there is a significant improvement of robot accuracy over a typical robot workspace.

Fast Calibration Method of Large Dimension Measurement System Based on Multi-Camera Array

2018 ◽  
Vol 38 (12) ◽  
pp. 1215002 ◽  
Author(s):  
吴庆华 Wu Qinghua ◽  
陈慧 Chen Hui ◽  
朱思斯 Zhu Sisi ◽  
周阳 Zhou Yang ◽  
万偲 Wan Cai
Keyword(s):  
Measurement System ◽  
Calibration Method ◽  
Large Dimension ◽  
Camera Array ◽  
Dimension Measurement

Simplified Calibration Method for Radiation Temperature Measurement System with Wide Dynamic Range

2019 ◽  
Vol 39 (6) ◽  
pp. 0612003
Author(s):  
马冬晓 Dongxiao Ma ◽  
汪家春 Jiachun Wang ◽  
陈宗胜 Zongsheng Chen ◽  
王冰 Bing Wang ◽  
刘洋 Yang Liu
Keyword(s):  
Temperature Measurement ◽  
Measurement System ◽  
Dynamic Range ◽  
Calibration Method ◽  
Radiation Temperature ◽  
Wide Dynamic Range ◽  
Temperature Measurement System

Calibration Method of Three-Dimensional Shape Measurement System Based on iGPS Positioning and Tracking

2019 ◽  
Vol 46 (1) ◽  
pp. 0104003
Author(s):  
马国庆 Ma Guoqing ◽  
刘丽 Liu Li ◽  
于正林 Yu Zhenglin ◽  
曹国华 Cao Guohua ◽  
王强 Wang Qiang
Keyword(s):  
Measurement System ◽  
Three Dimensional ◽  
Calibration Method ◽  
Shape Measurement ◽  
Dimensional Shape ◽  
Three Dimensional Shape

scholarly journals Extrinsic LiDAR/Ground Calibration Method Using 3D Geometrical Plane-Based Estimation

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2841
Author(s):  
Mohammad Ali Zaiter ◽  
Régis Lherbier ◽  
Ghaleb Faour ◽  
Oussama Bazzi ◽  
Jean-Charles Noyer
Keyword(s):  
Ground Plane ◽  
Ground Surface ◽  
Real Data ◽  
Calibration Method ◽  
Parameters Estimation ◽  
Parameters Optimization ◽  
Method Performance ◽  
Extrinsic Calibration ◽  
Extrinsic Parameters ◽  
The Stability

This paper details a new extrinsic calibration method for scanning laser rangefinder that is precisely focused on the geometrical ground plane-based estimation. This method is also efficient in the challenging experimental configuration of a high angle of inclination of the LiDAR. In this configuration, the calibration of the LiDAR sensor is a key problem that can be be found in various domains and in particular to guarantee the efficiency of ground surface object detection. The proposed extrinsic calibration method can be summarized by the following procedure steps: fitting ground plane, extrinsic parameters estimation (3D orientation angles and altitude), and extrinsic parameters optimization. Finally, the results are presented in terms of precision and robustness against the variation of LiDAR’s orientation and range accuracy, respectively, showing the stability and the accuracy of the proposed extrinsic calibration method, which was validated through numerical simulation and real data to prove the method performance.

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