scholarly journals Calibration Venus: An Interactive Camera Calibration Method Based on Search Algorithm and Pose Decomposition

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2170
Author(s):  
Wentai Lei ◽  
Mengdi Xu ◽  
Feifei Hou ◽  
Wensi Jiang ◽  
Chiyu Wang ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Camera Calibration ◽  
Search Algorithm ◽  
Calibration Method ◽  
Experimental Results ◽  
Major Task ◽  
Robot Positioning ◽  
User Guidance

Cameras are widely used in many scenes such as robot positioning and unmanned driving, in which the camera calibration is a major task in this field. The interactive camera calibration method based on a plane board is becoming popular due to its stability and handleability. However, most methods choose suggestions subjectively from a fixed pose dataset, which is error-prone and limited for different camera models. In addition, these methods do not provide clear guidelines on how to place the board in the specified pose. This paper proposes a new interactive calibration method, named ‘Calibration Venus’, including two main parts: pose search and pose decomposition. First, a pose search algorithm based on simulated annealing (SA) algorithm is proposed to select the optimal pose in the entire pose space. Second, an intuitive and easy-to-use user guidance method is designed to decompose the optimal pose into four sub-poses: translation, each rotation along X-, Y-, Z-axes. Thereby the users could follow the guide step by step to accurately complete the placement of the calibration board. Experimental results evaluated on simulated and real datasets show that the proposed method can reduce the difficulty of calibration, and improve the accuracy of calibration, as well as provide better guidance.

Camera Calibration Method Based on Vanishing Point

2014 ◽  
Vol 513-517 ◽  
pp. 3719-3722
Author(s):  
Wen Guo Li ◽  
Shao Jun Duan
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Experimental Results ◽  
Vanishing Point ◽  
Feature Points ◽  
Vanishing Points ◽  
Parallel Lines ◽  
Internal Parameters ◽  
The Matrix ◽  
Calibration Algorithm

We present a camera calibration method based on vanishing point, that is, the vanishing points of two groups of parallel lines on the target plane are used to achieve camera calibration. A series of known positions points on target plane are used as the feature points, and the target images are recorded, the image coordinates of feature points are used to calculate the coordinates of vanishing point, then the matrix between feature points and camera is used to obtain internal parameters of camera. Experimental results show that the proposed calibration algorithm is correct, simple and convenient.

A Novel Camera Calibration Method Based on Simulated Annealing Genetic Algorithm

2015 ◽  
Vol 719-720 ◽  
pp. 1184-1190
Author(s):  
Shuang Ran ◽  
Long Ye ◽  
Jing Ling Wang ◽  
Qin Zhang
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Camera Calibration ◽  
Simulated Annealing Algorithm ◽  
Image Plane ◽  
Calibration Method ◽  
Simulated Annealing Genetic Algorithm ◽  
Extrinsic Parameters ◽  
Annealing Algorithm ◽  
Intrinsic And Extrinsic Parameters

The optimization of the camera’s intrinsic and extrinsic parameters is a key step after obtaining the initialized parameters’ state by considering the homography between the board space plane and the image plane in Zhengyou Zhang method. In this paper, we proposed a camera calibration optimization algorithm by adopting genetic algorithm and the simulated annealing algorithm. The experiment results demonstrate that our algorithm can improve the precision of the camera calibration to a certain extent.

scholarly journals A Hybrid Cuckoo Search and Simulated Annealing Algorithm

2019 ◽  
Vol 28 (4) ◽  
pp. 683-698 ◽  
Author(s):  
Faisal Alkhateeb ◽  
Bilal H. Abed-alguni
Keyword(s):  
Simulated Annealing ◽  
Hybrid Algorithm ◽  
Simulated Annealing Algorithm ◽  
Performance Enhancement ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Search Space ◽  
Experimental Results ◽  
Efficient Manner ◽  
Optimization Search

Abstract Simulated annealing (SA) proved its success as a single-state optimization search algorithm for both discrete and continuous problems. On the contrary, cuckoo search (CS) is one of the well-known population-based search algorithms that could be used for optimizing some problems with continuous domains. This paper provides a hybrid algorithm using the CS and SA algorithms. The main goal behind our hybridization is to improve the solutions generated by CS using SA to explore the search space in an efficient manner. More precisely, we introduce four variations of the proposed hybrid algorithm. The proposed variations together with the original CS and SA algorithms were evaluated and compared using 10 well-known benchmark functions. The experimental results show that three variations of the proposed algorithm provide a major performance enhancement in terms of best solutions and running time when compared to CS and SA as stand-alone algorithms, whereas the other variation provides a minor enhancement. Moreover, the experimental results show that the proposed hybrid algorithms also outperform some well-known optimization algorithms.

scholarly journals Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nongeometric Errors

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yuxiang Wang ◽  
Zhangwei Chen ◽  
Hongfei Zu ◽  
Xiang Zhang ◽  
Chentao Mao ◽  
...  
Keyword(s):  
Neural Network ◽  
Manufacturing Systems ◽  
Robot Manipulator ◽  
Joint Stiffness ◽  
Calibration Method ◽  
Geometric Parameters ◽  
Heavy Load ◽  
Positioning Accuracy ◽  
Robot Positioning ◽  
Residual Errors

The positioning accuracy of a robot is of great significance in advanced robotic manufacturing systems. This paper proposes a novel calibration method for improving robot positioning accuracy. First of all, geometric parameters are identified on the basis of the product of exponentials (POE) formula. The errors of the reduction ratio and the coupling ratio are identified at the same time. Then, joint stiffness identification is carried out by adding a load to the end-effector. Finally, residual errors caused by nongeometric parameters are compensated by a multilayer perceptron neural network (MLPNN) based on beetle swarm optimization algorithm. The calibration is implemented on a SIASUN SR210D robot manipulator. Results show that the proposed method possesses better performance in terms of faster convergence and higher precision.

scholarly journals Cobot User Frame Calibration: Evaluation and Comparison between Positioning Repeatability Performances Achieved by Traditional and Vision-Based Methods

Robotics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 45
Author(s):  
Roberto Pagani ◽  
Cristina Nuzzi ◽  
Marco Ghidelli ◽  
Alberto Borboni ◽  
Matteo Lancini ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Production Line ◽  
Calibration Method ◽  
Fiducial Marker ◽  
Positioning System ◽  
Local Calibration ◽  
Calibration Methods ◽  
Robot Positioning ◽  
Good Repeatability ◽  
Calibration Time

Since cobots are designed to be flexible, they are frequently repositioned to change the production line according to the needs; hence, their working area (user frame) needs to be often calibrated. Therefore, it is important to adopt a fast and intuitive user frame calibration method that allows even non-expert users to perform the procedure effectively, reducing the possible mistakes that may arise in such contexts. The aim of this work was to quantitatively assess the performance of different user frame calibration procedures in terms of accuracy, complexity, and calibration time, to allow a reliable choice of which calibration method to adopt and the number of calibration points to use, given the requirements of the specific application. This has been done by first analyzing the performances of a Rethink Robotics Sawyer robot built-in user frame calibration method (Robot Positioning System, RPS) based on the analysis of a fiducial marker distortion obtained from the image acquired by the wrist camera. This resulted in a quantitative analysis of the limitations of this approach that only computes local calibration planes, highlighting the reduction of performances observed. Hence, the analysis focused on the comparison between two traditional calibration methods involving rigid markers to determine the best number of calibration points to adopt to achieve good repeatability performances. The analysis shows that, among the three methods, the RPS one resulted in very poor repeatability performances (1.42 mm), while the three and five points calibration methods achieve lower values (0.33 mm and 0.12 mm, respectively) which are closer to the reference repeatability (0.08 mm). Moreover, comparing the overall calibration times achieved by the three methods, it is shown that, incrementing the number of calibration points to more than five, it is not suggested since it could lead to a plateau in the performances, while increasing the overall calibration time.

Camera Calibration Method Based on Circle Plane Board

2013 ◽  
Vol 475-476 ◽  
pp. 184-187
Author(s):  
Wen Guo Li ◽  
Shao Jun Duan
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Lens Distortion ◽  
Edge Extraction ◽  
Circle Plane ◽  
Circle Centre ◽  
Extraction Algorithm ◽  
Calibration Algorithm ◽  
Characteristic Points ◽  
Distortion Parameters

We present a camera calibration method based on circle plane board. The centres of circles on plane are regarded as the characteristic points, which are used to implement camera calibration. The proposed calibration is more accurate than many previous calibration algorithm because of the merit of the coordinate of circle centre being obtained from thousand of of edge pionts of ellipse, which is very reliable to image noise caused by edge extraction algorithm. Experiments shows the proposed algorithm can obtain high precise inner parameters, and lens distortion parameters.

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