Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5128689 | Procedia Manufacturing | 2017 | 8 Pages |
Abstract
This research presents a method for the visual recognition of parts using machine learning services to enable the manipulation of complex parts. Robotic manipulation of complex parts is a challenging application due to the uncertainty of the parts' positioning as well as the gripper's grasping instability. This instability is caused by the non-symmetrical and complex geometries that may result in a slightly variable orientation of the part after being grasped, which is outside the handling/assembly process tolerance.To compensate for this, a visual recognition approach is implemented via classifiers. Finally, a case study focusing on the manipulation of consumer goods is demonstrated and evaluated.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Industrial and Manufacturing Engineering
Authors
P. Aivaliotis, A. Zampetis, G. Michalos, S. Makris,