Object recognition and automatic selection in a Robotic Sorting Cell
This thesis relates to the development of an automated sorting cell as part of a flexible manufacturing line, with the use of object recognition. Algorithms for each of the individual subsections creating the cell, recognition, position calculation and robot integration were developed and tested. The Fourier descriptors object recognition technique is investigated and used. Invariance to scale, rotation or translation of the boundary of an object recognition. Stereoscopy with basic trigonometry is used to calculate the position of recognised objects, after which they are handled by a robot. Integration of the robot into the project environment is done with trigonometry as well as Euler angles. It is shown that a successful, automated sorting cell can be constructed with object recognition. The results show that reliable sorting can be done with available hardware and the algorithms development.