A Vision-Based Self-Calibration Method for Robotic Visual Inspection Systems

A vision-based robot self-calibration method is proposed in this paper to evaluate the kinematic parameter errors of a robot using a visual sensor mounted on its end-effector. This approach could be performed in the industrial field without external, expensive apparatus or an elaborate setup. A robo...

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Main Authors: Shibin Yin, Yongjie Ren, Jigui Zhu, Shourui Yang, Shenghua Ye
Format: Article
Language:English
Published: MDPI AG 2013-12-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/13/12/16565
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author Shibin Yin
Yongjie Ren
Jigui Zhu
Shourui Yang
Shenghua Ye
author_facet Shibin Yin
Yongjie Ren
Jigui Zhu
Shourui Yang
Shenghua Ye
author_sort Shibin Yin
collection DOAJ
description A vision-based robot self-calibration method is proposed in this paper to evaluate the kinematic parameter errors of a robot using a visual sensor mounted on its end-effector. This approach could be performed in the industrial field without external, expensive apparatus or an elaborate setup. A robot Tool Center Point (TCP) is defined in the structural model of a line-structured laser sensor, and aligned to a reference point fixed in the robot workspace. A mathematical model is established to formulate the misalignment errors with kinematic parameter errors and TCP position errors. Based on the fixed point constraints, the kinematic parameter errors and TCP position errors are identified with an iterative algorithm. Compared to the conventional methods, this proposed method eliminates the need for a robot-based-frame and hand-to-eye calibrations, shortens the error propagation chain, and makes the calibration process more accurate and convenient. A validation experiment is performed on an ABB IRB2400 robot. An optimal configuration on the number and distribution of fixed points in the robot workspace is obtained based on the experimental results. Comparative experiments reveal that there is a significant improvement of the measuring accuracy of the robotic visual inspection system.
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spelling doaj.art-be05e0a9d5bd4cb0b2a9a99eebe867e92022-12-22T02:21:11ZengMDPI AGSensors1424-82202013-12-011312165651658210.3390/s131216565s131216565A Vision-Based Self-Calibration Method for Robotic Visual Inspection SystemsShibin Yin0Yongjie Ren1Jigui Zhu2Shourui Yang3Shenghua Ye4State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, ChinaState Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, ChinaState Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, ChinaState Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, ChinaState Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, ChinaA vision-based robot self-calibration method is proposed in this paper to evaluate the kinematic parameter errors of a robot using a visual sensor mounted on its end-effector. This approach could be performed in the industrial field without external, expensive apparatus or an elaborate setup. A robot Tool Center Point (TCP) is defined in the structural model of a line-structured laser sensor, and aligned to a reference point fixed in the robot workspace. A mathematical model is established to formulate the misalignment errors with kinematic parameter errors and TCP position errors. Based on the fixed point constraints, the kinematic parameter errors and TCP position errors are identified with an iterative algorithm. Compared to the conventional methods, this proposed method eliminates the need for a robot-based-frame and hand-to-eye calibrations, shortens the error propagation chain, and makes the calibration process more accurate and convenient. A validation experiment is performed on an ABB IRB2400 robot. An optimal configuration on the number and distribution of fixed points in the robot workspace is obtained based on the experimental results. Comparative experiments reveal that there is a significant improvement of the measuring accuracy of the robotic visual inspection system.http://www.mdpi.com/1424-8220/13/12/16565self-calibrationindustrial robotvisual sensorTCP
spellingShingle Shibin Yin
Yongjie Ren
Jigui Zhu
Shourui Yang
Shenghua Ye
A Vision-Based Self-Calibration Method for Robotic Visual Inspection Systems
Sensors
self-calibration
industrial robot
visual sensor
TCP
title A Vision-Based Self-Calibration Method for Robotic Visual Inspection Systems
title_full A Vision-Based Self-Calibration Method for Robotic Visual Inspection Systems
title_fullStr A Vision-Based Self-Calibration Method for Robotic Visual Inspection Systems
title_full_unstemmed A Vision-Based Self-Calibration Method for Robotic Visual Inspection Systems
title_short A Vision-Based Self-Calibration Method for Robotic Visual Inspection Systems
title_sort vision based self calibration method for robotic visual inspection systems
topic self-calibration
industrial robot
visual sensor
TCP
url http://www.mdpi.com/1424-8220/13/12/16565
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