Object detection and pose estimation of randomly organized objects for a robotic bin picking system
Independent thesis Advanced level (degree of Master (Two Years))Student thesis
Today modern industry systems are almost fully automated. The high requirements regarding speed, flexibility, precision and reliability makes it in some cases very difficult to create. One of the most willingly researched solution to solve many processes without human influence is bin-picking. Bin picking is a very complex process which integrates devices such as: robotic grasping arm, vision system, collision avoidance algorithms and many others. This paper describes the creation of a vision system - the most important part of the whole bin-picking system. Authors propose a model-based solution for estimating a best pick-up candidate position and orientation. In this method database is created from 3D CAD model, compared with processed image from the 3D scanner. Paper widely describes database creation from 3D STL model, Sick IVP 3D scanner configuration and creation of the comparing algorithm based on autocorrelation function and morphological operators. The results shows that proposed solution is universal, time efficient, robust and gives opportunities for further work.
Place, publisher, year, edition, pages
2013. , 65 p.
Bin-Picking, Object pose estimation, 3D image processing, Autocorrelation matching, Object detection
Computer Science Signal Processing Software Engineering
IdentifiersURN: urn:nbn:se:bth-2153Local ID: oai:bth.se:arkivexFA5E749E49371D49C1257B470062F4EAOAI: oai:DiVA.org:bth-2153DiVA: diva2:829421