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Robot task planning and explanation in open and uncertain worlds
University of Lincoln.
University of Freiburg.
University of Birmingham.
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0002-1396-0102
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2015 (English)In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921Article in journal (Refereed) Published
Abstract [en]

A long-standing goal of AI is to enable robots to plan in the face of uncertain and incomplete information, and to handle task failure intelligently. This paper shows how to achieve this. There are two central ideas. The first idea is to organize the robot's knowledge into three layers: instance knowledge at the bottom, commonsense knowledge above that, and diagnostic knowledge on top. Knowledge in a layer above can be used to modify knowledge in the layer(s) below. The second idea is that the robot should represent not just how its actions change the world, but also what it knows or believes. There are two types of knowledge effects the robot's actions can have: epistemic effects (I believe X because I saw it) and assumptions (I'll assume X to be true). By combining the knowledge layers with the models of knowledge effects, we can simultaneously solve several problems in robotics: (i) task planning and execution under uncertainty; (ii) task planning and execution in open worlds; (iii) explaining task failure; (iv) verifying those explanations. The paper describes how the ideas are implemented in a three-layer architecture on a mobile robot platform. The robot implementation was evaluated in five different experiments on object search, mapping, and room categorization.

Place, publisher, year, edition, pages
Elsevier, 2015.
Keyword [en]
Robotics
National Category
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-186868DOI: 10.1016/j.artint.2015.08.008OAI: oai:DiVA.org:kth-186868DiVA: diva2:928480
Projects
EU FP7 CogX
Funder
EU, FP7, Seventh Framework Programme, 215181Swedish Foundation for Strategic Research , RIT08-0010
Note

QC 20160517

Available from: 2016-05-16 Created: 2016-05-16 Last updated: 2016-05-17Bibliographically approved

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Publisher's full texthttp://www.sciencedirect.com/science/article/pii/S000437021500123X

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Pronobis, AndrzejSjöö, KristofferAydemir, AlperJensfelt, Patric
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Computer Vision and Active Perception, CVAPCentre for Autonomous Systems, CAS
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ReferencesLink to record
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