A new method for registration of heterogeneous sensors in a dimensional measurement system

Registration of multiple sensors is a basic step in multi-sensor dimensional or coordinate measuring systems before any measurement. In most cases, a common standard is used to be measured by all sensors, and this may work well for general registration of multiple homogeneous sensors. However, when inhomogeneous sensors detect a common standard, it is usually very difficult to obtain the same information, because of the different working principles of the sensors. In this paper, a new method called multiple steps registration is proposed to register two sensors: a video camera sensor (VCS) and a tactile probe sensor (TPS). In this method, the two sensors measure two separated standards: a chrome circle on a reticle and a reference sphere with a constant distance between them, fixed on a steel plate. The VCS captures only the circle and the TPS touches only the sphere. Both simulations and real experiments demonstrate that the proposed method is robust and accurate in the registration of multiple inhomogeneous sensors in a dimensional measurement system.

[1]  Feng Li,et al.  A practical coordinate unification method for integrated tactile–optical measuring system , 2014 .

[2]  Adam Wozniak,et al.  Proximity weighted correction of high density high uncertainty (HDHU) point cloud using low density low uncertainty (LDLU) reference point coordinates , 2015 .

[3]  Robert Schmitt,et al.  Geometric error measurement and compensation of machines : an update , 2008 .

[4]  Robert Sitnik,et al.  The hybrid contact–optical coordinate measuring system , 2011 .

[5]  S. Sartori,et al.  Geometric Error Measurement and Compensation of Machines , 1995 .

[6]  Massimo Pacella,et al.  Point set augmentation through fitting for enhanced ICP registration of point clouds in multisensor coordinate metrology , 2013 .

[7]  Wang Jianguo,et al.  Complete 3D measurement in reverse engineering using a multi-probe system , 2005 .

[8]  Kai Xue,et al.  Multi-sensor blue LED and touch probe inspection system , 2015 .

[9]  Chia-Hsiang Menq,et al.  Multiple-sensor integration for rapid and high-precision coordinate metrology , 2000 .

[10]  Yu Ding,et al.  Bayesian hierarchical model for combining misaligned two-resolution metrology data , 2011 .

[11]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[12]  Yunbao Huang,et al.  Multi-sensor calibration through iterative registration and fusion , 2009, Comput. Aided Des..

[13]  Jin Tao,et al.  A 3-D point sets registration method in reverse engineering , 2007, Comput. Ind. Eng..

[14]  Svenja Ettl,et al.  Automatic registration method for multisensor datasets adopted for dimensional measurements on cutting tools , 2013 .

[15]  V. H. Chan,et al.  A multi-sensor approach to automating co-ordinate measuring machine-based reverse engineering , 2001 .

[16]  Massimo Pacella,et al.  Multisensor data fusion via Gaussian process models for dimensional and geometric verification , 2015 .

[17]  A. Weckenmann,et al.  Automatic registration method for hybrid optical coordinate measuring technology , 2011 .

[18]  Zhong Chen,et al.  Telecentric stereo micro-vision system: Calibration method and experiments , 2014 .

[19]  Antony R Mileham,et al.  A New Data Fusion Method for Scanned Models , 2006, J. Comput. Inf. Sci. Eng..

[20]  Xiangqian Jiang,et al.  Multisensor data fusion in dimensional metrology , 2009 .