Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Caging Complex Objects with Geodesic Balls
Universität Stuttgart. (Machine Learning and Robotics Lab)
KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.ORCID-id: 0000-0003-1114-6040
Universität Stuttgart. (Machine Learning and Robotics Lab)
KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.ORCID-id: 0000-0003-2965-2953
2013 (engelsk)Inngår i: Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013), IEEE , 2013, s. 2999-3006Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

This paper proposes a novel approach for the synthesis of grasps of objects whose geometry can be observed only in the presence of noise. We focus in particular on the problem of generating caging grasps with a realistic robot hand simulation and show that our method can generate such grasps even on complex objects. We introduce the idea of using geodesic balls on the object's surface in order to approximate the maximal contact surface between a robotic hand and an object. We define two types of heuristics which extract information from approximate geodesic balls in order to identify areas on an object that can likely be used to generate a caging grasp. Our heuristics are based on two scoring functions. The first uses winding angles measuring how much a geodesic ball on the surface winds around a dominant axis, while the second explores using the total discrete Gaussian curvature of a geodesic ball to rank potential caging postures. We evaluate our approach with respect to variations in hand kinematics, for a selection of complex real-world objects and with respect to its robustness to noise.

sted, utgiver, år, opplag, sider
IEEE , 2013. s. 2999-3006
Serie
IEEE International Conference on Intelligent Robots and Systems. Proceedings, ISSN 2153-0858
Emneord [en]
Contact surface, Extract informations, Gaussian curvatures, Hand kinematics, Real-world objects, Realistic robots, Robustness to noise, Scoring functions
HSV kategori
Forskningsprogram
SRA - Informations- och kommunikationsteknik
Identifikatorer
URN: urn:nbn:se:kth:diva-129496DOI: 10.1109/IROS.2013.6696781ISI: 000331367403011Scopus ID: 2-s2.0-84893720249ISBN: 978-1-4673-6358-7 (tryckt)OAI: oai:DiVA.org:kth-129496DiVA, id: diva2:655671
Konferanse
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) November 3-7, 2013. Tokyo, Japan
Forskningsfinansiär
EU, FP7, Seventh Framework Programme, IST-FP7- 270436
Merknad

QC 20140128

Tilgjengelig fra: 2013-10-13 Laget: 2013-09-30 Sist oppdatert: 2018-01-11bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Andre lenker

Forlagets fulltekstScopuscsc.kth

Personposter BETA

Pokorny, Florian T.Kragic, Danica

Søk i DiVA

Av forfatter/redaktør
Pokorny, Florian T.Kragic, Danica
Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric

doi
isbn
urn-nbn
Totalt: 74 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf