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Autonomous meshing, texturing and recognition of object models with a mobile robot
KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.ORCID-id: 0000-0003-1189-6634
KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.ORCID-id: 0000-0002-7796-1438
KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.ORCID-id: 0000-0002-1170-7162
2017 (engelsk)Inngår i: 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) / [ed] Bicchi, A Okamura, A, IEEE , 2017, s. 5071-5078Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

We present a system for creating object models from RGB-D views acquired autonomously by a mobile robot. We create high-quality textured meshes of the objects by approximating the underlying geometry with a Poisson surface. Our system employs two optimization steps, first registering the views spatially based on image features, and second aligning the RGB images to maximize photometric consistency with respect to the reconstructed mesh. We show that the resulting models can be used robustly for recognition by training a Convolutional Neural Network (CNN) on images rendered from the reconstructed meshes. We perform experiments on data collected autonomously by a mobile robot both in controlled and uncontrolled scenarios. We compare quantitatively and qualitatively to previous work to validate our approach.

sted, utgiver, år, opplag, sider
IEEE , 2017. s. 5071-5078
Serie
IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-225806DOI: 10.1109/IROS.2017.8206391ISI: 000426978204127Scopus ID: 2-s2.0-85041961210ISBN: 978-1-5386-2682-5 (tryckt)OAI: oai:DiVA.org:kth-225806DiVA, id: diva2:1196060
Konferanse
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), SEP 24-28, 2017, Vancouver, CANADA
Forskningsfinansiär
EU, FP7, Seventh Framework Programme, 600623Swedish Foundation for Strategic Research Swedish Research Council, C0475401
Merknad

QC 20180409

Tilgjengelig fra: 2018-04-09 Laget: 2018-04-09 Sist oppdatert: 2020-03-05bibliografisk kontrollert

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Ambrus, RaresBore, NilsFolkesson, JohnJensfelt, Patric

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