Method of Constructing a System of Optical Sensors for Mutual Orientation of Industrial Robots for Monitoring of the Technosphere Objects

Purpose Developing of the methods of relative orientation of industrial robots and construction of three-dimensional scenes areas of interest using optical sensors. Results Developed the method of construction of the relative orientation of industrial robots to meet the challenges of reconstruction of three-dimensional mapping and image-set received from the optical sensors. The basis of this technique is the problem of finding the solution of the global position of each industrial robot on the relative orientation of each of them. The global position of the industrial robot characterized by a matrix of rotation and transfer vector in a coordinate system (adopted as a global). As a result of the global positioning possible to solve the major problems of vision such as detection, tracking and classification of objects of the space in which these systems and robots operate. Practical significance Continuous qualitative monitoring of technosphere objects.

[1]  Venu Madhav Govindu,et al.  Combining two-view constraints for motion estimation , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[2]  Tomás Pajdla,et al.  Robust Rotation and Translation Estimation in Multiview Reconstruction , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[3]  Carsten Rother Linear multiview reconstruction of points, lines, planes and cameras using a reference plane , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[4]  Yoel Shkolnisky,et al.  Three-Dimensional Structure Determination from Common Lines in Cryo-EM by Eigenvectors and Semidefinite Programming , 2011, SIAM J. Imaging Sci..

[5]  Andrew Zisserman,et al.  Robust Detection of Degenerate Configurations while Estimating the Fundamental Matrix , 1998, Comput. Vis. Image Underst..

[6]  H. C. Longuet-Higgins,et al.  A computer algorithm for reconstructing a scene from two projections , 1981, Nature.

[7]  Jochen Trumpf,et al.  L1 rotation averaging using the Weiszfeld algorithm , 2011, CVPR 2011.

[8]  Carl Olsson,et al.  Non-sequential structure from motion , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[9]  A. Hoffman,et al.  Some metric inequalities in the space of matrices , 1955 .

[10]  A. Singer Angular Synchronization by Eigenvectors and Semidefinite Programming. , 2009, Applied and computational harmonic analysis.

[11]  Richard I. Hartley,et al.  Multiple-View Geometry Under the {$L_\infty$}-Norm , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Andrew Owens,et al.  Discrete-continuous optimization for large-scale structure from motion , 2011, CVPR.