Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/716995
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dc.contributor.authorPolychronis Kondaxakis|Khurram Gulzar|Stefan Kinauer|Iasonas Kokkinos|Ville Kyrkien_US
dc.date.accessioned2013en_US
dc.date.accessioned2021-05-16T17:43:33Z-
dc.date.available2021-05-16T17:43:33Z-
dc.date.issueden_US
dc.identifier.isbn1552-3098en_US
dc.identifier.other10.1109/TRO.2018.2875388en_US
dc.identifier.urihttp://localhost/handle/Hannan/716995-
dc.description.abstractIn a multirobot system, using shared symbols for objects in the environment is a prerequisite for collaboration. Sharing symbols requires that each agent has anchored a symbol with an internal, sensor level representation, as well as that these symbols match between the agents. The problem can be solved easily when the internal representations can be communicated between the agents. However, with heterogeneous embodiments the available sensors are likely to differ, making it impossible to share the internal representations directly. We propose the use of pointing gestures to align symbols between a heterogeneous group of robots. We describe a planning framework that minimizes the required effort for anchoring representations across robots. The framework allows planning for both the gesturing and observing agents in a decentralized fashion. It considers both implicit sources of failure, such as ambiguous pointing, as well as costs required by actions. Simulation experiments demonstrate that the resulting planning problem has a complex solution structure with multiple local minima. Demonstration with a heterogeneous two-robot system shows the practical viability of this approach.en_US
dc.relation.haspart08502843.pdfen_US
dc.subjectCognitive robotics|multi-robot systems|symbol groundingen_US
dc.titleRobot–Robot Gesturing for Anchoring Representationsen_US
dc.title.alternativeIEEE Transactions on Roboticsen_US
dc.typeArticleen_US
dc.journal.volumeVolumeen_US
dc.journal.issueIssueen_US
dc.journal.titleIEEE Transactions on Roboticsen_US
Appears in Collections:New Ieee 2019

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dc.contributor.authorPolychronis Kondaxakis|Khurram Gulzar|Stefan Kinauer|Iasonas Kokkinos|Ville Kyrkien_US
dc.date.accessioned2013en_US
dc.date.accessioned2021-05-16T17:43:33Z-
dc.date.available2021-05-16T17:43:33Z-
dc.date.issueden_US
dc.identifier.isbn1552-3098en_US
dc.identifier.other10.1109/TRO.2018.2875388en_US
dc.identifier.urihttp://localhost/handle/Hannan/716995-
dc.description.abstractIn a multirobot system, using shared symbols for objects in the environment is a prerequisite for collaboration. Sharing symbols requires that each agent has anchored a symbol with an internal, sensor level representation, as well as that these symbols match between the agents. The problem can be solved easily when the internal representations can be communicated between the agents. However, with heterogeneous embodiments the available sensors are likely to differ, making it impossible to share the internal representations directly. We propose the use of pointing gestures to align symbols between a heterogeneous group of robots. We describe a planning framework that minimizes the required effort for anchoring representations across robots. The framework allows planning for both the gesturing and observing agents in a decentralized fashion. It considers both implicit sources of failure, such as ambiguous pointing, as well as costs required by actions. Simulation experiments demonstrate that the resulting planning problem has a complex solution structure with multiple local minima. Demonstration with a heterogeneous two-robot system shows the practical viability of this approach.en_US
dc.relation.haspart08502843.pdfen_US
dc.subjectCognitive robotics|multi-robot systems|symbol groundingen_US
dc.titleRobot–Robot Gesturing for Anchoring Representationsen_US
dc.title.alternativeIEEE Transactions on Roboticsen_US
dc.typeArticleen_US
dc.journal.volumeVolumeen_US
dc.journal.issueIssueen_US
dc.journal.titleIEEE Transactions on Roboticsen_US
Appears in Collections:New Ieee 2019

Files in This Item:
File Description SizeFormat 
08502843.pdf7.31 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorPolychronis Kondaxakis|Khurram Gulzar|Stefan Kinauer|Iasonas Kokkinos|Ville Kyrkien_US
dc.date.accessioned2013en_US
dc.date.accessioned2021-05-16T17:43:33Z-
dc.date.available2021-05-16T17:43:33Z-
dc.date.issueden_US
dc.identifier.isbn1552-3098en_US
dc.identifier.other10.1109/TRO.2018.2875388en_US
dc.identifier.urihttp://localhost/handle/Hannan/716995-
dc.description.abstractIn a multirobot system, using shared symbols for objects in the environment is a prerequisite for collaboration. Sharing symbols requires that each agent has anchored a symbol with an internal, sensor level representation, as well as that these symbols match between the agents. The problem can be solved easily when the internal representations can be communicated between the agents. However, with heterogeneous embodiments the available sensors are likely to differ, making it impossible to share the internal representations directly. We propose the use of pointing gestures to align symbols between a heterogeneous group of robots. We describe a planning framework that minimizes the required effort for anchoring representations across robots. The framework allows planning for both the gesturing and observing agents in a decentralized fashion. It considers both implicit sources of failure, such as ambiguous pointing, as well as costs required by actions. Simulation experiments demonstrate that the resulting planning problem has a complex solution structure with multiple local minima. Demonstration with a heterogeneous two-robot system shows the practical viability of this approach.en_US
dc.relation.haspart08502843.pdfen_US
dc.subjectCognitive robotics|multi-robot systems|symbol groundingen_US
dc.titleRobot–Robot Gesturing for Anchoring Representationsen_US
dc.title.alternativeIEEE Transactions on Roboticsen_US
dc.typeArticleen_US
dc.journal.volumeVolumeen_US
dc.journal.issueIssueen_US
dc.journal.titleIEEE Transactions on Roboticsen_US
Appears in Collections:New Ieee 2019

Files in This Item:
File Description SizeFormat 
08502843.pdf7.31 MBAdobe PDFThumbnail
Preview File