Augmented Reality Control of the Telerobot 2003



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3.2 MODULE SPECIFICATION


The first step of the camera calibration was to obtain an image of the ABB operating environment, especially of the grid where the ABB operates on. The image of the operating environment can be attained from the image capture software.

Secondly, the control inputs both for the 3D operating environment and its corresponding image coordinates must be determined. The coordinate of the 3D control points can be determined through the use of a reference coordinate defined upon the operating environment.

As for the control points for the image coordinates, it would be rather difficult and cumbersome if the orientation of the camera is always changing. Therefore, assuming that the camera is stationary throughout the calibration module, the image control points can then be evaluated from the centre of projection.

Generally, the control points are chosen to be stationary or prominent targets. In this instance, the control points would most ideally be chosen as the end points of the grid or at least where two grid lines intersect each other. Using this solution, the relationship between both the sets of control points can be easily evaluated.



An example of the control points can be observed as follows:



Figure 14

Example of control points of the image coordinates

From Figure 14, the red dot can be treated as control points input either from the user or predetermined. As one will realise, the selection of those coordinates are much prominent to other target coordinates.



Once the inputs for the camera calibration module have been attained, the effort to solve for the camera calibration matrix itself can be realised. The program structure for the camera calibration module can be depicted as follows:



Figure 3: Program structure for solving the camera calibration matrix, C

where the inputs are defined as:



  • 2D image of the actual 3D operating environment.

  • XYZ coordinates of the control target points in the 3D operating environment.

  • UV coordinates of the control target points in the 2D image.

along with the following outputs:

  • The camera calibration matrix, C.

  • The error on satisfying the calibration constraints.

From Figure 3, it is realised that there is an additional output to the camera calibration matrix C, which is the error output log. The error output details information pertaining to the constraints of satisfying the calibration.

With the arbitrary scale of the camera calibration matrix, the main measure of the error in satisfying the camera matrix constraints is the value of , as highlight in Equation 21.

3.3 IMPLEMENTATION ISSUES


The module was initially developed in Matlab rather than LabView mainly due to the reason that most advice in the development of the camera calibration came from Dr. Peter Kovesi, a computer science lecturer specialising in image analysis, and he was mainly correlating the materials in Matlab.

Although Matlab can be integrated with LabView through a formula function node, the issue mainly falls to the architecture design of the calibration module in Matlab. Even after several attempt in the module integration with LabView, the integration still failed to meet the desired design specification.

Secondly, most of the team members lack the knowledge of image calibration. There are indeed many materials and advice but the team still lacks the understanding the fully utilised the camera calibration matrix.

3.4 TEST SPECIFICATION


  1. Check the image coordinate control points for a given coordinate frame and origin of the image.

  2. Evaluate the sequence of the 3D coordinate points correlate with the image coordinate control points.

  3. Evaluate the algorithms to solve for the elements of matrix B.

  4. Evaluate the pseudo-inverse solution of matrix B in determining the camera calibration matrix C.





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