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.

A Self-Calibration Method for Robotic Measurement System

1999 ◽  
Vol 122 (1) ◽  
pp. 174-181 ◽  
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

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. [S1087-1357(00)01301-0]

scholarly journals IMU-Based Online Kinematic Calibration of Robot Manipulator

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Guanglong Du ◽  
Ping Zhang
Keyword(s):  
Kalman Filter ◽  
Robot Manipulator ◽  
Experimental Studies ◽  
Estimation Method ◽  
Kinematic Parameter ◽  
Corner Detection ◽  
Measurement Unit ◽  
Robot Calibration ◽  
Self Calibration ◽  
Calibration Methods

Robot calibration is a useful diagnostic method for improving the positioning accuracy in robot production and maintenance. An online robot self-calibration method based on inertial measurement unit (IMU) is presented in this paper. The method requires that the IMU is rigidly attached to the robot manipulator, which makes it possible to obtain the orientation of the manipulator with the orientation of the IMU in real time. This paper proposed an efficient approach which incorporates Factored Quaternion Algorithm (FQA) and Kalman Filter (KF) to estimate the orientation of the IMU. Then, an Extended Kalman Filter (EKF) is used to estimate kinematic parameter errors. Using this proposed orientation estimation method will result in improved reliability and accuracy in determining the orientation of the manipulator. Compared with the existing vision-based self-calibration methods, the great advantage of this method is that it does not need the complex steps, such as camera calibration, images capture, and corner detection, which make the robot calibration procedure more autonomous in a dynamic manufacturing environment. Experimental studies on a GOOGOL GRB3016 robot show that this method has better accuracy, convenience, and effectiveness than vision-based methods.

scholarly journals A Novel AVM Calibration Method Using Unaligned Square Calibration Boards

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2265
Author(s):  
Jung Hyun Lee ◽  
Dong-Wook Lee
Keyword(s):  
Coordinate System ◽  
Reference Data ◽  
Side Information ◽  
Reference Sample ◽  
Likelihood Estimation ◽  
Calibration Method ◽  
World Coordinate System ◽  
Sample Data ◽  
The World ◽  
Left And Right

An around view monitoring (AVM) system acquires the front, rear, left, and right-side information of a vehicle using four cameras and transforms the four images into one image coordinate system to monitor around the vehicle with one image. Conventional AVM calibration utilizes the maximum likelihood estimation (MLE) to determine the parameters that can transform the captured four images into one AVM image. The MLE requires reference data of the image coordinate system and the world coordinate system to estimate these parameters. In conventional AVM calibration, many aligned calibration boards are placed around the vehicle and are measured to extract the reference sample data. However, accurately placing and measuring the calibration boards around a vehicle is an exhaustive procedure. To remediate this problem, we propose a novel AVM calibration method that requires only four randomly placed calibration boards by estimating the location of each calibration board. First, we define the AVM errors and determine the parameters that minimize the error in estimating the location. We then evaluate the accuracy of the proposed method through experiments using a real-sized vehicle and an electric vehicle for children to show that the proposed method can generate an AVM image similar to the conventional AVM calibration method regardless of a vehicle’s size.

Parallel Robot Calibration Utilizing Adaptronic Joints

2008 ◽  
Author(s):  
Philipp Last ◽  
Annika Raatz ◽  
Ju¨rgen Hesselbach ◽  
Nenad Pavlovic ◽  
Ralf Keimer
Keyword(s):  
Parallel Robot ◽  
Parallel Robots ◽  
Machine Component ◽  
Robot Calibration ◽  
Geometric Calibration ◽  
Self Calibration ◽  
Mechanical Constraints ◽  
Special Machine ◽  
Calibration Methods ◽  
Calibration Techniques

Model based geometric calibration is well known to be an efficient way to enhance absolute accuracy of robotic systems. Generally its application requires redundant measurements, which are achieved by external metrology equipment in most traditional calibration techniques. However, these methods are usually time-consuming, expensive and inconvenient. Thus, so-called self-calibration methods have achieved attention from researchers, which either use internal sensors or rely on mechanical constraints instead. In this paper a new self-calibration technique is presented for parallel robots which is motivated by the idea of constrained calibration. The new approach utilizes a special machine component called the adaptronic swivel joint in order to achieve the required redundant information. Compared to similar approaches it offers several advantages. The new calibration scheme is described and verified in simulation studies using a RRRRR-structure as an example.

scholarly journals An Online Calibration Method for a Galvanometric System Based on Wavelet Kernel ELM

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1353 ◽  
Author(s):  
Wugang Zhang ◽  
Wei Guo ◽  
Chuanwei Zhang ◽  
Shuanfeng Zhao
Keyword(s):  
Real Time ◽  
Calibration Method ◽  
System Structure ◽  
Data Sets ◽  
Position Measurement ◽  
Online Calibration ◽  
Time Performance ◽  
Calibration Methods ◽  
Testing Data ◽  
Mean Square Errors

The online calibration method of a two-dimensional (2D) galvanometer requires both high precision and better real-time performance to meet the needs of moving target position measurement, which presents some challenges for traditional calibration methods. In this paper, a new online calibration method is proposed using the wavelet kernel extreme learning machine (KELM). Firstly, a system structure is created and its experiment setup is established. The online calibration method is then analyzed based on a wavelet KELM algorithm. Finally, the acquisition methods of the training data are set, two groups of testing data sets are presented, and the verification method is described. The calibration effects of the existing methods and wavelet KELM methods are compared in terms of both accuracy and speed. The results show that, for the two testing data sets, the root mean square errors (RMSE) of the Mexican Hat wavelet KELM are reduced by 16.4% and 38.6%, respectively, which are smaller than that of the original ELM, and the standard deviations (Sd) are reduced by 19.2% and 36.6%, respectively, indicating the proposed method has better generalization and noise suppression performance for the nonlinear samples of the 2D galvanometer. Although the online operation time of KELM is longer than ELM, due to the complexity of the wavelet kernel, it still has better real-time performance.

scholarly journals Study on Comprehensive Calibration and Image Sieving for Coal-Gangue Separation Parallel Robot

2020 ◽  
Vol 10 (20) ◽  
pp. 7059
Author(s):  
Deyong Shang ◽  
Yuwei Wang ◽  
Zhiyuan Yang ◽  
Junjie Wang ◽  
Yue Liu
Keyword(s):  
Coordinate System ◽  
Image Recognition ◽  
Calculation Method ◽  
Calibration Method ◽  
Parallel Robot ◽  
Recognition System ◽  
Conveyor Belt ◽  
Coal Gangue ◽  
Experimental Results ◽  
Robot Calibration

Online sorting robots based on image recognition are key pieces of equipment for the intelligent washing of coal mines. In this paper, a Delta-type, coal gangue sorting, parallel robot is designed to automatically identify and sort scattered coal and gangue on conveyor belts by configuring the image recognition system. Robot calibration technology can reduce the influence of installation error on system accuracy and provides the basis for the robot to accurately track and grab gangue. Due to the fact that the angle deflection error between the conveyor belt coordinate system and the robot coordinate system is not considered in the traditional conveyor belt calibration method, an improved comprehensive calibration method is put forward in this paper. Firstly, the working principle and image recognition and positioning process of the Delta coal gangue sorting robot are introduced. The scale factor parameter Factorc of the conveyor encoder is adopted to characterize the relationship between the moving distance of the conveyor and the encoder. The conveyor belt calibration experiment is described in detail. The transformation matrix between the camera, the conveyor belt, and the robot are obtained after establishment of the three respective coordinate systems. The experimental results show that the maximum cumulative deviation of traditional calibration method is 13.841 mm and the comprehensive calibration method is 3.839 mm. The main innovation of the comprehensive calibration is such that the accurate position of each coordinate in the robot coordinate system can be determined. This comprehensive calibration method is simple and feasible, and can effectively improve system calibration accuracy and reduce robot installation error on the grasping accuracy. Moreover, a calculation method to eliminate duplicate images is put forward, with the frame rate of the vision system set at seven frames per second to avoid image repetition acquisition and missing images. The experimental results show that this calculation method effectively improves the processing efficiency of the recognition system, thereby meeting the demands of the grab precision of coal gangue separation engineering. The goal revolving around “safety with few people and safety with none” can therefore be achieved in coal gangue sorting using robots.

scholarly journals Base Detection Research of Drilling Robot System by Using Visual Inspection

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Zhanxi Wang ◽  
Jing Bai ◽  
Xiaoyu Zhang ◽  
Xiansheng Qin ◽  
Xiaoqun Tan ◽  
...  
Keyword(s):  
Coordinate System ◽  
Light Source ◽  
Measurement System ◽  
Visual Inspection ◽  
Displacement Sensor ◽  
Hole Drilling ◽  
Laser Displacement Sensor ◽  
Robot System ◽  
Visual Measurement ◽  
Drilling System

This paper expounds the principle and method of calibration and base detection by using the visual measurement system for detection and correction of installation error between workpiece and the robot drilling system. This includes the use of Cognex Insight 5403 high precision industrial camera, a light source, and the KEYENCE coaxial IL-300 laser displacement sensor. The three-base holes method and two-base holes method are proposed to analyze the transfer relation between the basic coordinate system of the actual hole drilling robot and the basic coordinate system of the theoretical hole drilling robot. The corresponding vision coordinates calibration and the base detection experiments are examined and the data indicate that the result of base detection is close to the correct value.

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.

Accuracy calibration of a 3-CRU translational parallel robot based on the subset of error measurements

2020 ◽  
pp. 095440622096769
Author(s):  
Tie Zhang ◽  
Guangcai Ma ◽  
Yachao Cao ◽  
Yingwu He
Keyword(s):  
Linear Combination ◽  
Error Compensation ◽  
Calibration Method ◽  
Parallel Robot ◽  
Laser Tracker ◽  
End Effector ◽  
Structural Error ◽  
Robot Accuracy ◽  
Calibration Methods ◽  
Complete Set

Robot accuracy calibration is an effective method to improve its kinematic accuracy. However, most of the existing calibration methods need to measure the complete set of 6-dimensional pose errors of the end-effector, which makes the calibration process especially complicated. In this paper, an accuracy calibration method for a 3-CRU translational parallel robot is proposed based on the subset of error measurements. The process is implemented by four steps: 1) the error model is established based on matrix method. Then the structural errors to be identified are separated. 2) part of pose errors of the end-effector are measured by laser tracker and used to form the subset of error measurements. 3) the minimum structural error linear combination affecting robot accuracy is determined according to the minimum parameter error linear combination theorem. After that, the structural errors can be identified based on the subset of error measurements. 4) error compensation based on the identification results. This method can not only ensure the identifiability of the structural errors, but also can realize error identification based on the subset of error measurements, which will significantly reduce the calibration workload and improve the calibration efficiency. Experiments are carried out to prove the effectiveness of the calibration method.

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