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Integrating Object and Grasp Recognition for Dynamic Scene interpretation
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0003-2965-2953
2005 (English)In: Advanced Robotics, ISSN 0169-1864, E-ISSN 1568-5535Article in journal (Refereed) Published
Abstract [en]

Understanding and interpreting dynamic scenes and activities is a very challenging problem. In this paper, we present a system capable of learning robot tasks from demonstration. Classical robot task programming requires an experienced programmer and a lot of tedious work. In contrast, programming by demonstration is a flexible framework that reduces the complexity of programming robot tasks, and allows end-users to demonstrate the tasks instead of writing code. We present our recent steps towards this goal. A system for learning pick-and-place tasks by manually demonstrating them is presented. Each demonstrated task is described by an abstract model involving a set of simple tasks such as what object is moved, where it is moved, and which grasp type was used to move it

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Computer and Information Science
URN: urn:nbn:se:kth:diva-82408OAI: diva2:498210
QC 20120305Available from: 2012-02-11 Created: 2012-02-11 Last updated: 2012-03-05Bibliographically approved

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