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Chapter

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Title

CNNs for State Estimation of Articulated Objects

Authors

[ 1 ] Instytut Robotyki i Inteligencji Maszynowej, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.2] Automation, electronics, electrical engineering and space technologies

Year of publication

2022

Chapter type

chapter in monograph / paper

Publication language

english

Keywords
EN
  • articulated objects
  • robot perception
  • deep learning in robotics
Abstract

EN In this paper, we deal with the problem of state estimation of articulated objects during robotic interaction. The robot equipped with an RGB-D camera has to estimate the joint position and rotation of the articulated object when manipulating the object. The problem of accurate state estimation is challenging due to the properties of the RGB-D sensor. The known solutions require some assumptions about the shape of the objects. In this paper, we propose the application of Convolutional Neural Networks to the state estimation of articulated objects from two pairs of RGB-D images.

Pages (from - to)

112 - 115

URL

https://wydawnictwo.umg.edu.pl/pp-rai2022/pdfs/26_pp-rai-2022-072.pdf

Book

Proceedings of the 3rd Polish Conference on Artificial Intelligence PP-RAI'2022, April 25-27, 2022, Gdynia, Poland

Presented on

3rd Polish Conference on Artificial Intelligence PP-RAI'2022, 25-27.04.2022, Gdynia, Polska

Ministry points / chapter

20

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