Robot learning of everyday object manipulations via human demonstration Dang Hao author Columbia University. Computer Science Allen Peter K. author Columbia University. Computer Science Columbia University. Computer Science originator text Articles 2010 English We deal with the problem of teaching a robot to manipulate everyday objects through human demonstration. We first design a task descriptor which encapsulates important elements of a task. The design originates from observations that manipulations involved in many everyday object tasks can be considered as a series of sequential rotations and translations, which we call manipulation primitives. We then propose a method that enables a robot to decompose a demonstrated task into sequential manipulation primitives and construct a task descriptor. We also show how to transfer a task descriptor learned from one object to similar objects. In the end, we argue that this framework is highly generic. Particularly, it can be used to construct a robot task database that serves as a manipulation knowledge base for a robot to succeed in manipulating everyday objects. Robotics The IEEE/RSJ International Conference on Intelligent Robots and Systems: IROS 2010: Taipei International Convention Center, Taipei, Taiwan, October 18-22, 2010: conference proceedings Piscataway, N.J. IEEE 2010 1284 1289 http://dx.doi.org/10.1109/IROS.2010.5651244 </titleInfo> </relatedItem> </relatedItem> <identifier type="hdl">http://hdl.handle.net/10022/AC:P:15083</identifier> <location> <physicalLocation authority="marcorg">NNC</physicalLocation> </location> <recordInfo> <recordContentSource authority="marcorg">NNC</recordContentSource> <recordCreationDate encoding="w3cdtf">2012-10-25 14:55:32 -0400</recordCreationDate> <recordChangeDate encoding="w3cdtf">2012-10-25 15:02:34 -0400</recordChangeDate> <recordIdentifier>9081</recordIdentifier> <languageOfCataloging> <languageTerm authority="iso639-2b">eng</languageTerm> </languageOfCataloging> </recordInfo> </mods>