Influence of human factor in the AACMM performance: a new evaluation methodology

González-Madruga, D.; Barreiro, J.; Cuesta, E.; Martínez-Pellitero, Susana

doi:10.1007/s12541-014-0468-9

Cited by 15 publications

(17 citation statements)

References 22 publications

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“…Finally, frame O 2 L is rotated about z 2 L by À =2 and about x 3 L by À, so that the laser beam shots toward key point P i , as indicated in Figure 6(c). Thus, the relationship between frame O 3 L and frame O B is…”

Section: Laser Displacement Sensor Shootingmentioning

confidence: 99%

“…Firstly, the location accuracy of key points in frame O B is depended on the location accuracy of C P si influenced by parameters l si , u i , v i , u 0 , v 0 , f x , f y , which will be analyzed in ''Location error caused by parameters'' section. Secondly, while executing laser displacement sensor shooting, because of robot positioning error, hand-eye error (represented by C T T) and error of transformation L C T, practical position and orientation of laser displacement sensor frame (donated as frame O 4 L ) may not coincide with its theoretical frame O 3 L , and the transformation between those two frames is denoted by L4 L3 T. Location error caused by L4 L3 T is analyzed in ''Distance error caused by L4 L3 T'' section. It should be mentioned that laser beam may not shoot on key point when locating quite thin tube, and a scan strategy is proposed to deal with this problem in ''Scan strategy of laser displacement sensor'' section.…”

Section: Coordinate Calculationmentioning

confidence: 99%

“…Articulated arm coordinate measuring machines (AACMM) is also applied to tube measurement because of its excellent dexterity, such as Romer (Hexagon company). 3 Unfortunately, it takes a lot of manpower, because an operator needs to hold the AACMM to acquire enough points. To achieve automatic measurement, Grimson et al 1 have presented a system including laser scanner and four-axis gantry, which mainly consists of four steps (rough localization, scan planning, dense point cloud scanning, and inspection) and has emphasized on analyzing rough localization.…”

Section: Introductionmentioning

confidence: 99%

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Design and calibration of a three-dimensional localization system for automatic measurement of long and thin tube based on camera and laser displacement sensor

Zhuang

Gao

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part C:

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An integrated system consisting of robot and laser scanner is considered as a promising alternative measurement device for three-dimensional tube which is long and thin. A key to achieving automatic measurement is to locate tube accurately and robustly, which is precondition for scanning path planning. Thus, a novel three-dimensional localization system consisting of camera and laser displacement senor is proposed. When fixed on robot, the camera can search tube quickly in large view and the laser displacement sensor obtains depth information of key points. Measurement principles are presented firstly, including four main steps: camera shooting, key points extraction, laser displacement sensor shooting, and coordinate calculation. Then, the location error influenced by parameters of camera model and laser displacement sensor is analyzed and illustrated by a specific camera and laser displacement sensor. Furthermore, a scan strategy is proposed for quite thin tube localization. Location error caused by perspective is also analyzed and a compensation method is proposed for decreasing the error. Additionally, a sensor transformation calibration method is presented for identifying the relationship between camera and laser displacement sensor, which is verified with high accuracy by calibration experiments. A contrast experiment of a cylinder bar localization shows that the maximum location error of the camera and laser displacement sensor is no more than 3.5 mm, which is only one-eighth of that of Kinect sensor. The mean and maximum location errors are within 2 mm and 3 mm when locating a car brake and fuel tube with about 1300 mm long, indicating high accuracy and good robustness of designed localization system.

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Section: Laser Displacement Sensor Shootingmentioning

confidence: 99%

Section: Coordinate Calculationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Design and calibration of a three-dimensional localization system for automatic measurement of long and thin tube based on camera and laser displacement sensor

Zhuang

Gao

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

show abstract

“…Modeling Error Analysis. It is known that the accuracy of the AACMM is affected greatly by the manufacture, assembly, and component selection [21,22], which can all result in inconsistence between the structural parameters in the kinematic model and the actual ones. However, the proposed identification method in this paper can achieve high accuracy for AACMM modeling without increasing the cost to construct the parts and buy extra sensors.…”

Section: Identification For Aacmm Uncertain Parametersmentioning

confidence: 99%

Structural Parameter Identification of Articulated Arm Coordinate Measuring Machines

Gao

Zhang

Guo

2016

Mathematical Problems in Engineering

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Precise structural parameter identification of a robotic articulated arm coordinate measuring machine (AACMM) is essential for improving its measuring accuracy, particularly in robotic applications. This paper presents a constructive parameter identification approach for robotic AACMMs. We first develop a mathematical kinematic model of the AACMM based on the Denavit-Hartenberg (DH) approach established for robotic systems. This model is further calibrated and verified via the practical test data. Based on the difference between the calculated coordinates of the AACMM probe via the kinematic model and the given reference coordinates, a parameter identification approach is proposed to estimate the structural parameters in terms of the test data set. The Jacobian matrix is further analyzed to determine the solvability of the identification model. It shows that there are two coupling parameters, which can be removed in the regressor. Finally, a parameter identification algorithm taking the least-square solution of the identification model as the structural parameters by using the obtained poses data is suggested. Practical experiments based on a robotic AACMM test rig are carried out, and the results reveal the effectiveness and robustness of the proposed identification approach.

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“…Based on the above literature review, the existing evaluation models include single feature evaluation, multi-feature weight fuzzy evaluation and multi-feature fusion evaluation. Single feature evaluation cannot fully reflect the production system [ 20 ]; objectivity and fairness are weak in multi-feature weight fuzzy evaluation [ 21 ]; and multi feature fusion, widely used in fault detection, is another good evaluation method for service quality. Multi-feature fusion cannot make full use of all the feature information.…”

Section: Introductionmentioning

confidence: 99%

Process service quality evaluation based on Dempster-Shafer theory and support vector machine

Pei

Tong

et al. 2017

PLoS ONE

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Human involvement influences traditional service quality evaluations, which triggers an evaluation’s low accuracy, poor reliability and less impressive predictability. This paper proposes a method by employing a support vector machine (SVM) and Dempster-Shafer evidence theory to evaluate the service quality of a production process by handling a high number of input features with a low sampling data set, which is called SVMs-DS. Features that can affect production quality are extracted by a large number of sensors. Preprocessing steps such as feature simplification and normalization are reduced. Based on three individual SVM models, the basic probability assignments (BPAs) are constructed, which can help the evaluation in a qualitative and quantitative way. The process service quality evaluation results are validated by the Dempster rules; the decision threshold to resolve conflicting results is generated from three SVM models. A case study is presented to demonstrate the effectiveness of the SVMs-DS method.

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Influence of human factor in the AACMM performance: a new evaluation methodology

Cited by 15 publications

References 22 publications

Design and calibration of a three-dimensional localization system for automatic measurement of long and thin tube based on camera and laser displacement sensor

Design and calibration of a three-dimensional localization system for automatic measurement of long and thin tube based on camera and laser displacement sensor

Structural Parameter Identification of Articulated Arm Coordinate Measuring Machines

Process service quality evaluation based on Dempster-Shafer theory and support vector machine

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