Rapid and Precise Reverse Engineering of Complex Geometry Through Multi-Sensor Data Fusion
This paper presents an effective multi-sensor approach for improving the accuracy of laser scanner by using a tactile probe to perform rapid and accurate reverse engineering of complex objects. The proposed system is unique in that it includes not only the physical integration of the two digitizers...
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doaj-a415710078ee4e1ba60733e5e86c3a612021-03-29T23:01:17ZengIEEEIEEE Access2169-35362019-01-01716579316581310.1109/ACCESS.2019.29481248873591Rapid and Precise Reverse Engineering of Complex Geometry Through Multi-Sensor Data FusionZhiqiang Yu0https://orcid.org/0000-0001-7577-7015Taiyong Wang1https://orcid.org/0000-0002-7820-7699Peng Wang2Ying Tian3Hongbin Li4Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, ChinaKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, ChinaKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, ChinaKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, ChinaKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, ChinaThis paper presents an effective multi-sensor approach for improving the accuracy of laser scanner by using a tactile probe to perform rapid and accurate reverse engineering of complex objects. The proposed system is unique in that it includes not only the physical integration of the two digitizers but also their combination at the measurement information level. With the coordinate data acquired using the optical scanner, intelligent data segmentation and feature recognition algorithm are proposed to divide the original point set into geometric elements and free-form surfaces. The tactile probe is guided to re-measure each feature with a small number of sampling points. Then different data fusion algorithms are proposed to compensate the scanned data patches of geometric features and free-form features with the accurate tactile probing data. Finally, the compensated point data can be exploited for accurate reverse engineering of a CAD model. Through the fusion of different sensor's information, both sensors complement each other with their advantages. Experimental results show that for the measurement of geometric surface, the proposed method can improve the accuracy of optical measurement to the accuracy of contact measurement. For free-form surface measurement, the proposed method reduces the optical measurement error from +0.032/-0.019 mm to ±0.016 mm, and the standard deviation from 0.012 mm to 0.004 mm. The measurement efficiency of proposed method is 4.5 times higher than that of contact measurement alone.https://ieeexplore.ieee.org/document/8873591/Multi-sensorreverse engineeringtactile probeoptical scannerdata fusion |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhiqiang Yu Taiyong Wang Peng Wang Ying Tian Hongbin Li |
spellingShingle |
Zhiqiang Yu Taiyong Wang Peng Wang Ying Tian Hongbin Li Rapid and Precise Reverse Engineering of Complex Geometry Through Multi-Sensor Data Fusion IEEE Access Multi-sensor reverse engineering tactile probe optical scanner data fusion |
author_facet |
Zhiqiang Yu Taiyong Wang Peng Wang Ying Tian Hongbin Li |
author_sort |
Zhiqiang Yu |
title |
Rapid and Precise Reverse Engineering of Complex Geometry Through Multi-Sensor Data Fusion |
title_short |
Rapid and Precise Reverse Engineering of Complex Geometry Through Multi-Sensor Data Fusion |
title_full |
Rapid and Precise Reverse Engineering of Complex Geometry Through Multi-Sensor Data Fusion |
title_fullStr |
Rapid and Precise Reverse Engineering of Complex Geometry Through Multi-Sensor Data Fusion |
title_full_unstemmed |
Rapid and Precise Reverse Engineering of Complex Geometry Through Multi-Sensor Data Fusion |
title_sort |
rapid and precise reverse engineering of complex geometry through multi-sensor data fusion |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
This paper presents an effective multi-sensor approach for improving the accuracy of laser scanner by using a tactile probe to perform rapid and accurate reverse engineering of complex objects. The proposed system is unique in that it includes not only the physical integration of the two digitizers but also their combination at the measurement information level. With the coordinate data acquired using the optical scanner, intelligent data segmentation and feature recognition algorithm are proposed to divide the original point set into geometric elements and free-form surfaces. The tactile probe is guided to re-measure each feature with a small number of sampling points. Then different data fusion algorithms are proposed to compensate the scanned data patches of geometric features and free-form features with the accurate tactile probing data. Finally, the compensated point data can be exploited for accurate reverse engineering of a CAD model. Through the fusion of different sensor's information, both sensors complement each other with their advantages. Experimental results show that for the measurement of geometric surface, the proposed method can improve the accuracy of optical measurement to the accuracy of contact measurement. For free-form surface measurement, the proposed method reduces the optical measurement error from +0.032/-0.019 mm to ±0.016 mm, and the standard deviation from 0.012 mm to 0.004 mm. The measurement efficiency of proposed method is 4.5 times higher than that of contact measurement alone. |
topic |
Multi-sensor reverse engineering tactile probe optical scanner data fusion |
url |
https://ieeexplore.ieee.org/document/8873591/ |
work_keys_str_mv |
AT zhiqiangyu rapidandprecisereverseengineeringofcomplexgeometrythroughmultisensordatafusion AT taiyongwang rapidandprecisereverseengineeringofcomplexgeometrythroughmultisensordatafusion AT pengwang rapidandprecisereverseengineeringofcomplexgeometrythroughmultisensordatafusion AT yingtian rapidandprecisereverseengineeringofcomplexgeometrythroughmultisensordatafusion AT hongbinli rapidandprecisereverseengineeringofcomplexgeometrythroughmultisensordatafusion |
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