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CAD-Based Pose Estimation - Algorithm Investigation
Linköpings universitet, Institutionen för systemteknik, Datorseende.
2019 (engelsk)Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
Abstract [en]

One fundamental task in robotics is random bin-picking, where it is important to be able to detect an object in a bin and estimate its pose to plan the motion of a robotic arm. For this purpose, this thesis work aimed to investigate and evaluate algorithms for 6D pose estimation when the object was given by a CAD model. The scene was given by a point cloud illustrating a partial 3D view of the bin with multiple instances of the object. Two algorithms were thus implemented and evaluated. The first algorithm was an approach based on Point Pair Features, and the second was Fast Global Registration. For evaluation, four different CAD models were used to create synthetic data with ground truth annotations.

It was concluded that the Point Pair Feature approach provided a robust localization of objects and can be used for bin-picking. The algorithm appears to be able to handle different types of objects, however, with small limitations when the object has flat surfaces and weak texture or many similar details. The disadvantage with the algorithm was the execution time. Fast Global Registration, on the other hand, did not provide a robust localization of objects and is thus not a good solution for bin-picking.

sted, utgiver, år, opplag, sider
2019. , s. 53
Emneord [en]
6D pose estimation, bin-picking, point cloud, Point Pair Feature, Fast Global Registration
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-157776ISRN: LiTH-ISY-EX--19/5239--SEOAI: oai:DiVA.org:liu-157776DiVA, id: diva2:1330419
Eksternt samarbeid
SICK IVP
Fag / kurs
Computer Vision Laboratory
Presentation
2019-06-11, Algoritmen, 08:15 (engelsk)
Veileder
Examiner
Tilgjengelig fra: 2019-06-26 Laget: 2019-06-25 Sist oppdatert: 2019-06-26bibliografisk kontrollert

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