Coordinate alignment of combined measurement systems using a modified common points method

The co-ordinate metrology has been extensively researched for its outstanding advantages in measurement range and accuracy. The alignment of different measurement systems is usually achieved by integrating local coordinates via common points before measurement. The alignment errors would accumulate and significantly reduce the global accuracy, thus need to be minimized. In this thesis, a modified common points method (MCPM) is proposed to combine different traceable system errors of the cooperating machines, and optimize the global accuracy by introducing mutual geometric constraints. The geometric constraints, obtained by measuring the common points in individual local coordinate systems, provide the possibility to reduce the local measuring uncertainty whereby enhance the global measuring certainty. A simulation system is developed in Matlab to analyze the feature of MCPM using the Monto-Carlo method. An exemplary setup is constructed to verify the feasibility and efficiency of the proposed method associated with laser tracker and indoor iGPS systems. Experimental results show that MCPM could significantly improve the alignment accuracy.