scholarly journals Extrinsic Calibration of 2D Laser Rangefinders Based on a Mobile Sphere

2018 ◽  
Vol 10 (8) ◽  
pp. 1176 ◽  
Author(s):  
Shoubin Chen ◽  
Jingbin Liu ◽  
Teng Wu ◽  
Wenchao Huang ◽  
Keke Liu ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Three Dimensional ◽  
Calibration Method ◽  
High Accuracy ◽  
Sensor Data ◽  
Extrinsic Calibration ◽  
Practical Applications ◽  
Calibration Methods ◽  
Simultaneous Location And Mapping ◽  
Automatic Matching

In the fields of autonomous vehicles, virtual reality and three-dimensional (3D) reconstruction, 2D laser rangefinders have been widely employed for different purposes, such as localization, mapping, and simultaneous location and mapping. However, the extrinsic calibration of multiple 2D laser rangefinders is a fundamental prerequisite for guaranteeing their performance. In contrast to existing calibration methods that rely on manual procedures or suffer from low accuracy, an automatic and high-accuracy solution is proposed in this paper for the extrinsic calibration of 2D laser rangefinders. In the proposed method, a mobile sphere is used as a calibration target, thereby allowing the automatic extrapolation of a spherical center and the automatic matching of corresponding points. Based on the error analysis, a matching machine of corresponding points with a low error is established with the restriction constraint of the scan circle radius, thereby achieving the goal of high-accuracy calibration. Experiments using the Hokuyo UTM-30LX sensor show that the method can increase the extrinsic orientation accuracy to a sensor intrinsic accuracy of 10 mm without requiring manual measurements or manual correspondence among sensor data. Therefore, the calibration method in this paper is automatic, highly accurate, and highly effective, and it meets the requirements of practical applications.

scholarly journals Calibration of Binocular Vision Sensors Based on Unknown-Sized Elliptical Stripe Images

2017 ◽  
Author(s):  
Zhen Liu ◽  
Suining Wu ◽  
Yang Yin ◽  
Jinbo Wu
Keyword(s):  
Optical Filter ◽  
Optical Filters ◽  
Calibration Method ◽  
High Accuracy ◽  
Feature Points ◽  
Physical Experiments ◽  
Binocular Stereo Vision ◽  
Vision Sensors ◽  
Calibration Methods ◽  
Binocular Stereo

Most of the existing calibration methods for binocular stereo vision sensor (BSVS) depend on high-accuracy target with feature points that are difficult to manufacture and costly. In complex light conditions, optical filters are used for BSVS, but they affect imaging quality. Hence, the use of a high-accuracy target with certain-sized feature points for calibration is not feasible under such complex conditions. To solve these problems, a calibration method based on unknown-sized elliptical stripe images is proposed. With known intrinsic parameters, the proposed method adopts the elliptical stripes located on the parallel planes as a medium to calibrate BSVS online. In comparison with the common calibration methods, the proposed method avoids utilizing high-accuracy target with certain-sized feature points. Therefore, the proposed method is not only easy to implement but is a realistic method for the calibration of BSVS with optical filter. Changing the size of elliptical curves projected on the target solves the difficulty of applying the proposed method in different fields of view and distances. Simulative and physical experiments are conducted to validate the efficiency of the proposed method. When the field of view is approximately 400 mm × 300 mm, the proposed method can reach a calibration accuracy of 0.03 mm, which is comparable with that of Zhang’s method.

The Calibration Method of a stereo-Vision-Based Coordinates Measurement System via a Two-Axis Turntable--The Combination of Stereo Vision and Turntable

2021 ◽  
Vol 14 ◽  
Author(s):  
Zimiao Zhang ◽  
Zhiwu Wang ◽  
Shihai Zhang ◽  
Anqi Fu
Keyword(s):  
Stereo Vision ◽  
Measurement System ◽  
Vision System ◽  
Three Dimensional ◽  
Calibration Method ◽  
Measurement Range ◽  
Measurement Technology ◽  
Rotation Axes ◽  
Internal Parameters ◽  
Calibration Methods

Background: Stereo-vision-based three-dimensional coordinates measurement technology has been widely applied in the military or civil fields. There are two problems that need to be solved. The first problem is that each camera internal parameters and the two cameras external parameters need to be calibrated. To increase the measurement range, usually the turntable is used with the stereo vision system together. The second problem is the calibration of the turntable. Objective: The aim of the study is to construct and calibrate a stereo-vision-based coordinates measurement system via a two-axis turntable. Methods: Considering that the internal parameters of each camera do not change during the measurement process and the complicated optimization process of one-step self-calibration, a two-step stereo vision calibration method is proposed. In the first step, we calibrate the internal parameters of each camera through a specially designed planar target with circular points. In the second step, on the basis of the calibrated results of the internal parameters, the two cameras external parameters are calibrated through a simple target which could be distributed in the measurement volume. For the calibration of the two-axis turntable, we calibrated the rotation axes of the turntable and the coordinates of points in the 3D space could be measured considering the non-orthogonality of the axes. Results: Some experiments are provided to examine the calibration methods we proposed. They are the plane target measurement experiments, the standard ball center coordinates measurement experiments and target pose measurement experiments. Experiment results demonstrate the superiority of the calibration method we proposed. Conclusion: We studied the calibration methods of the stereo-vision-based coordinates measurement system via a two-axis turntable. The experimental results show the measurement accuracy of our system is less than 0.1mm.

scholarly journals Extrinsic Calibration of Multiple Two-Dimensional Laser Rangefinders Based on a Trihedron

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1837 ◽  
Author(s):  
Fei Zhu ◽  
Yuchun Huang ◽  
Zizhu Tian ◽  
Yaowei Ma
Keyword(s):  
Autonomous Vehicles ◽  
Laser Scanning ◽  
Mobile Robotics ◽  
Three Dimensional ◽  
Point Problem ◽  
Two Dimensional ◽  
Simple Method ◽  
Extrinsic Calibration ◽  
Dimensional Reconstruction ◽  
Special Pattern

Multiple two-dimensional laser rangefinders (LRFs) are applied in many applications like mobile robotics, autonomous vehicles, and three-dimensional reconstruction. The extrinsic calibration between LRFs is the first step to perform data fusion and practical application. In this paper, we proposed a simple method to calibrate LRFs based on a corner composed of three mutually perpendicular planes. In contrast to other methods that require a special pattern or assistance from other sensors, the trihedron corner needed in this method is common in daily environments. In practice, we can adjust the position of the LRFs to observe the corner until the laser scanning plane intersects with three planes of the corner. Then, we formed a Perspective-Three-Point problem to solve the position and orientation of each LRF at the common corner coordinate system. The method was validated with synthetic and real experiments, showing better performance than existing methods.

scholarly journals Performance Index for Extrinsic Calibration of LiDAR and Motion Sensor for Mapping and Localization

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 106
Author(s):  
Gamin Kim
Keyword(s):  
Performance Index ◽  
Autonomous Vehicles ◽  
Three Dimensional ◽  
Real Data ◽  
Motion Sensor ◽  
Extrinsic Calibration ◽  
Calibration Parameter ◽  
True Value ◽  
A Value ◽  
Surrounding Environment

Light Detection and Ranging (LiDAR) is a sensor that uses a laser to represent the surrounding environment in three-dimensional information. Thanks to the development of LiDAR, LiDAR-based applications are being actively used in autonomous vehicles. In order to effectively use the information coming from LiDAR, extrinsic calibration which finds the translation and the rotation relationship between LiDAR coordinate and vehicle coordinate is essential. Therefore, many studies on LiDAR extrinsic calibration are steadily in progress. The performance index (PI) of the calibration parameter is a value that quantitatively indicates whether the obtained calibration parameter is similar to the true value or not. In order to effectively use the obtained calibration parameter, it is important to validate the parameter through PI. Therefore, in this paper, we propose an algorithm to obtain the performance index for the calibration parameter between LiDAR and the motion sensor. This performance index is experimentally verified in various environments by Monte Carlo simulation and validated using CarMaker simulation data and real data. As a result of verification, the PI of the calibration parameter obtained through the proposed algorithm has the smallest value when the calibration parameter has a true value, and increases as an error is added to the true value. In other words, it has been proven that PI is convex to the calibration parameter. In addition, it is able to confirm that the PI obtained using the proposed algorithm provides information on the effect of the calibration parameters on mapping and localization.

scholarly journals A Novel IMU Extrinsic Calibration Method for Mass Production Land Vehicles

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 7
Author(s):  
Vicent Rodrigo Marco ◽  
Jens Kalkkuhl ◽  
Jörg Raisch ◽  
Thomas Seel
Keyword(s):  
Motion Estimation ◽  
Sensor Fusion ◽  
Calibration Method ◽  
Estimation Problem ◽  
Sensor Data ◽  
Measurement Unit ◽  
Coordinate Systems ◽  
Extrinsic Calibration ◽  
Adaptive Estimator ◽  
Precise Knowledge

Multi-modal sensor fusion has become ubiquitous in the field of vehicle motion estimation. Achieving a consistent sensor fusion in such a set-up demands the precise knowledge of the misalignments between the coordinate systems in which the different information sources are expressed. In ego-motion estimation, even sub-degree misalignment errors lead to serious performance degradation. The present work addresses the extrinsic calibration of a land vehicle equipped with standard production car sensors and an automotive-grade inertial measurement unit (IMU). Specifically, the article presents a method for the estimation of the misalignment between the IMU and vehicle coordinate systems, while considering the IMU biases. The estimation problem is treated as a joint state and parameter estimation problem, and solved using an adaptive estimator that relies on the IMU measurements, a dynamic single-track model as well as the suspension and odometry systems. Additionally, we show that the validity of the misalignment estimates can be assessed by identifying the misalignment between a high-precision INS/GNSS and the IMU and vehicle coordinate systems. The effectiveness of the proposed calibration procedure is demonstrated using real sensor data. The results show that estimation accuracies below 0.1 degrees can be achieved in spite of moderate variations in the manoeuvre execution.

scholarly journals Improve three-dimensional point localization accuracy in stereo vision systems using a novel camera calibration method

2020 ◽  
Vol 17 (1) ◽  
pp. 172988141989671 ◽  
Author(s):  
Luis R Ramírez-Hernández ◽  
Julio C Rodríguez-Quiñonez ◽  
Moises J Castro-Toscano ◽  
Daniel Hernández-Balbuena ◽  
Wendy Flores-Fuentes ◽  
...  
Keyword(s):  
Camera Calibration ◽  
Stereo Vision ◽  
Autonomous Navigation ◽  
Three Dimensional ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Vision Systems ◽  
Localization Accuracy ◽  
Calibration Methods

Computer vision systems have demonstrated to be useful in applications of autonomous navigation, especially with the use of stereo vision systems for the three-dimensional mapping of the environment. This article presents a novel camera calibration method to improve the accuracy of stereo vision systems for three-dimensional point localization. The proposed camera calibration method uses the least square method to model the error caused by the image digitalization and the lens distortion. To obtain particular three-dimensional point coordinates, the stereo vision systems use the information of two images taken by two different cameras. Then, the system locates the two-dimensional pixel coordinates of the three-dimensional point in both images and coverts them into angles. With the obtained angles, the system finds the three-dimensional point coordinates through a triangulation process. The proposed camera calibration method is applied in the stereo vision systems, and a comparative analysis between the real and calibrated three-dimensional data points is performed to validate the improvements. Moreover, the developed method is compared with three classical calibration methods to analyze their advantages in terms of accuracy with respect to tested methods.

scholarly journals Calibration of Short Range 2D Laser Range Finder for 3D SLAM Usage

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Petr Olivka ◽  
Michal Krumnikl ◽  
Pavel Moravec ◽  
David Seidl
Keyword(s):  
Short Range ◽  
Three Dimensional ◽  
Ground Truth ◽  
Calibration Method ◽  
Calibration Procedure ◽  
High Angular Resolution ◽  
Laser Range Finder ◽  
Range Finder ◽  
Laser Range ◽  
Practical Applications

The laser range finder is one of the most essential sensors in the field of robotics. The laser range finder provides an accurate range measurement with high angular resolution. However, the short range scanners require an additional calibration to achieve the abovementioned accuracy. The calibration procedure described in this work provides an estimation of the internal parameters of the laser range finder without requiring any special three-dimensional targets. This work presents the use of a short range URG-04LX scanner for mapping purposes and describes its calibration. The precision of the calibration was checked in an environment with known ground truth values and the results were statistically evaluated. The benefits of the calibration are also demonstrated in the practical applications involving the segmentation of the environment. The proposed calibration method is complex and detects all major manufacturing inaccuracies. The procedure is suitable for easy integration into the current manufacturing process.

Development of a 6-Channel Power Controller for Simultaneous Actuation and Resistance Measurement of SMA Wires

2010 ◽  
Author(s):  
Rohan Hangekar ◽  
Stephen Furst ◽  
Stefan Seelecke
Keyword(s):  
Joule Heating ◽  
Position Control ◽  
Optimization Techniques ◽  
Sensor Data ◽  
Channel Power ◽  
Practical Applications ◽  
North Carolina State University ◽  
Power Controller ◽  
Calibration Methods ◽  
The Wire

The use of ‘multifunctional’ Shape Memory Alloy wires as embedded actuators and sensors has been proposed for numerous novel applications. The SMA wires are actuated as a result of the Joule heating induced by passing electric current through it. The resistance of the SMA wire can simultaneously be measured during its actuation enabling it to be used as sensor data that relates to the strain and temperature of the wire. In order to control actuation stroke from the SMA wire, the Joule heating (electric power supplied to the SMA wire) of the wire needs to be controlled. Therefore, a 6-channel power controller device has been developed that simultaneously controls the power supplied to six different SMA wires and measures the resistance of these wires during excitation. This paper continues from the previously presented concept of a multi-channel power controller implementation. The focus of this paper is to discuss the operation, calibration methods and optimization techniques to improve the performance and robustness of the device and to eliminate the issues in multi-channel implementation. Further, this device is implemented in a test setup to study the position control of SMA wire using resistance feedback. Results of these tests can be utilized in practical applications involving SMA wires as embedded actuators and sensors, such as Smart Inhaler system being developed at North Carolina State University.

A New Extrinsic Calibration Method of Three-Dimensional Imaging Lidar and Camera

2011 ◽  
Vol 58-60 ◽  
pp. 2194-2199
Author(s):  
Hong Wei Jiao ◽  
Shi Qiao Qin ◽  
Chun Sheng Hu ◽  
Xing Shu Wang
Keyword(s):  
Three Dimensional ◽  
Texture Mapping ◽  
Ccd Camera ◽  
Calibration Method ◽  
Lidar Data ◽  
Color Information ◽  
Three Dimensional Imaging ◽  
Extrinsic Calibration ◽  
Calibration Process ◽  
Reverse Mapping

Three-dimensional imaging lidar can offer the range information and CCD camera can offer the color information of the target. These two information can strongly supplement each other, the fusion of them is becoming a research hot point. The major problem of fusing lidar data and camera data is the coordinate calibration between them. In consideration of the traits of lidar and camera, a new planar object calibration method was proposed, which solves extrinsic matrix using the normal of planar objects. The rotation matrix and transfer vector are solved separately, which can simplify the calibration process and highly improve the calibration precision. The improved extrinsic calibration method was applied on texture mapping and reverse mapping, which show that our algorithm can gives good results.

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