Title :
Detection, localization and picking up of coil springs from a pile
Author :
Ono, Keishi ; Ogawa, Tomomi ; Maeda, Yuji ; Nakatani, Shigeki ; Nagayasu, Go ; Shimizu, Ryosuke ; Ouchi, N.
fDate :
May 31 2014-June 7 2014
Abstract :
Picking of parts loaded in bulk is an industrial need. Thus bin-picking systems for various objects have ever been studied by various ways. However, it is difficult to recognize coil springs randomly placed in a pile by conventional machine vision techniques because of their shape characteristics. In this paper, we propose a method of recognition and pose estimation of coil springs. This method uses their highlights made by illumination for their recognition and pose estimation with stereo vision. We implemented this method as a bin-picking system with an industrial robot. Bin-picking of coil springs was successfully demonstrated on the system. Position errors were less than 2 mm. The average success rate for a coil spring in the part box was 94% when multiple retrials of picking were allowed. This rate could be improved by implementation of collision avoidance.
Keywords :
collision avoidance; industrial robots; materials handling; object detection; pose estimation; robot vision; springs (mechanical); stereo image processing; bin-picking systems; coil springs detection; coil springs localization; coil springs pick-up; coil springs pose estimation; coil springs recognition; collision avoidance; industrial robot; machine vision techniques; parts picking; pile; shape characteristics; stereo vision; Cameras; Coils; Estimation; Image matching; Image recognition; Shape; Springs;
Conference_Titel :
Robotics and Automation (ICRA), 2014 IEEE International Conference on
Conference_Location :
Hong Kong
DOI :
10.1109/ICRA.2014.6907360