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http://dx.doi.org/10.18419/opus-3337
Autor(en): | Zielke, Viktor |
Titel: | Instance-based learning of affordances |
Erscheinungsdatum: | 2014 |
Dokumentart: | Studienarbeit |
URI: | http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-94219 http://elib.uni-stuttgart.de/handle/11682/3354 http://dx.doi.org/10.18419/opus-3337 |
Zusammenfassung: | The discovery of possible interactions with objects is a vital part of an exploration task for robots. An important subset of these possible interactions are affordances. Affordances describe what a specific object can afford to a specific agent, based on the capabilities of the agent and the properties of the object in relation to the agent. For example, a chair affords a human to be sat-upon, if the sitting area of the chair is approximately knee-high. In this work, an instance-based learning approach is made to discover these affordances solely through different visual representations of point cloud data of an object. The point clouds are acquired with a Microsoft Kinect sensor. Different representations are tested and evaluated against a set of point cloud data of various objects found in a living room environment. |
Enthalten in den Sammlungen: | 05 Fakultät Informatik, Elektrotechnik und Informationstechnik |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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STUD_2443.pdf | 2,66 MB | Adobe PDF | Öffnen/Anzeigen |
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