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.

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.

Modeling and Calibration of Grid Structured Light Based 3-D Vision Inspection

1999 ◽  
Vol 122 (4) ◽  
pp. 734-738 ◽  
Author(s):  
Guangjun Zhang ◽  
Liqun Ma
Keyword(s):  
Mathematical Model ◽  
Coordinate System ◽  
Structured Light ◽  
Calibration Method ◽  
Experimental Results ◽  
Image Feature ◽  
Feature Analysis ◽  
Calibration Process ◽  
Vision Inspection ◽  
The Mathematical Model

The principle of structured light 3-D vision is introduced, and using projective and perspective transformations, the mathematical model of grid structured light based 3-D vision inspection is established in homogeneous coordinate system in this paper. Based on the image feature analysis of grid structured light, a calibration method of grid structured light based 3-D vision inspection is proposed, and experimental results are also presented. This method is easy, efficient and fast to carry out. It simplifies the calibration process while guaranteeing its accuracy. [S1087-1357(00)00703-6]

Recognition System for Fatigue Facial Expression of Driver

2014 ◽  
Vol 644-650 ◽  
pp. 4174-4177
Author(s):  
Xue Mei Wang ◽  
Jia Jun Zhang
Keyword(s):  
Facial Expression ◽  
Image Recognition ◽  
Detection Method ◽  
Recognition Rate ◽  
Recognition System ◽  
Attention Mechanism ◽  
Experimental Results ◽  
Feature Points ◽  
Driver Fatigue ◽  
Recognition Model

In order to improve the accuracy of recognition system for fatigue facial expression of driver, driver fatigue expression of this paper, the detection method for key feature points in the fatigue facial expression image of driver is applied in the paper to establish a fatigue expression image recognition model based on attention mechanism. Experimental results show that the algorithm can improve the recognition rate of driver's expression image, so as to record fatigue expression image of driver more accurate.

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]

Blasting Hole Recognition and Location Based on Machine Vision

2015 ◽  
Vol 733 ◽  
pp. 718-721 ◽  
Author(s):  
Cong Ping Chen ◽  
Zheng Huang
Keyword(s):  
Machine Vision ◽  
Coordinate System ◽  
Calibration Method ◽  
Experimental Results ◽  
Detection Accuracy ◽  
Location Method ◽  
High Detection ◽  
Hole Position ◽  
Camera Coordinate System

In order to guide the manipulator putting explosive into the blasting hole automatically, a hole recognition and location method based on machine vision is presented. First, capture the target blasting hole pictures from two different directions by a camera mounted on the manipulator. Then, use binocular calibration method to get the hole position based on the camera coordinate. Finally, transform the camera coordinate system to the manipulator coordinate system, and then the target hole position is obtained. The experimental results show that this method has high detection accuracy and achieves a better blasting hole location.

Calibration Methods of Planar Parallel Robot

2011 ◽  
Vol 464 ◽  
pp. 340-343
Author(s):  
Wei Da Li ◽  
Juan Li ◽  
Li Ning Sun
Keyword(s):  
Error Compensation ◽  
Calibration Method ◽  
Parallel Robot ◽  
Position Error ◽  
Experimental Results ◽  
Kinematic Calibration ◽  
Absolute Position ◽  
Position Accuracy ◽  
Calibration Methods ◽  
Means Of Measurement

Kinematic calibration is an effective method of improving robotic absolute position accuracy by means of measurement, identification and compensation etc. This paper investigates the technology of kinematic calibration and error compensation for the 2-DOF planar parallel robot. A multi-step calibration method is presented based on error itterative method and nonlinear optimum method. Experimental results indicate that the proposed method can effectively compensate position error of the robot in Oxy plane, and the absolute position error of the calibrated robot is less than 6μm.

scholarly journals Intelligent Recognition System Based on Contour Accentuation for Navigation Marks

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yanke Du ◽  
Shuo Sun ◽  
Shi Qiu ◽  
Shaoxi Li ◽  
Mingyang Pan ◽  
...  
Keyword(s):  
Image Recognition ◽  
Recognition Accuracy ◽  
Multiple Scale ◽  
Recognition System ◽  
Attention Mechanism ◽  
Important Task ◽  
Experimental Results ◽  
Classification Model ◽  
Navigation Systems ◽  
Intelligent Recognition

Sensing navigational environment represented by navigation marks is an important task for unmanned ships and intelligent navigation systems, and the sensing can be performed by recognizing the images from a camera. In order to improve the image recognition accuracy, this paper combined a contour accentuation algorithm into a multiple scale attention mechanism-based classification model for navigation marks. Experimental results show that the method increases the accuracy of navigation mark classification from 95.98% to 96.53%. Based on the classification model, an intelligent navigation mark recognition system was developed for the Changjiang Nanjing Waterway Bureau, in which the model is deployed and updated by the TensorFlow Serving.

scholarly journals Research of Calibration Method for Industrial Robot Based on Error Model of Position

2021 ◽  
Vol 11 (3) ◽  
pp. 1287
Author(s):  
Tianyan Chen ◽  
Jinsong Lin ◽  
Deyu Wu ◽  
Haibin Wu
Keyword(s):  
Coordinate System ◽  
Industrial Robot ◽  
Calibration Method ◽  
Error Model ◽  
Position Error ◽  
Industrial Robots ◽  
Positioning Error ◽  
Robot Position ◽  
General Measurement ◽  
Parameter Error

Based on the current situation of high precision and comparatively low APA (absolute positioning accuracy) in industrial robots, a calibration method to enhance the APA of industrial robots is proposed. In view of the "hidden" characteristics of the RBCS (robot base coordinate system) and the FCS (flange coordinate system) in the measurement process, a comparatively general measurement and calibration method of the RBCS and the FCS is proposed, and the source of the robot terminal position error is classified into three aspects: positioning error of industrial RBCS, kinematics parameter error of manipulator, and positioning error of industrial robot end FCS. The robot position error model is established, and the relation equation of the robot end position error and the industrial robot model parameter error is deduced. By solving the equation, the parameter error identification and the supplementary results are obtained, and the method of compensating the error by using the robot joint angle is realized. The Leica laser tracker is used to verify the calibration method on ABB IRB120 industrial robot. The experimental results show that the calibration method can effectively enhance the APA of the robot.

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