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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

Place, publisher, year, edition, pages
2005.
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-82408OAI: oai:DiVA.org:kth-82408DiVA: diva2:498210
Note
QC 20120305Available from: 2012-02-11 Created: 2012-02-11 Last updated: 2017-12-07Bibliographically approved

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Kragic, Danica

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