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AI Reasoning Methods for Robotics
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-9652-7864
2016 (English)In: Springer Handbook of Robotics / [ed] Bruno Siciliano, Oussama Khatib, Springer, 2016, 2, p. 329-356Chapter in book (Other academic)
Abstract [en]

Artificial intelligence (AI) reasoning technology involving, e.g., inference, planning, and learning, has a track record with a healthy number of successful applications. So can it be used as a toolbox of methods for autonomous mobile robots? Not necessarily, as reasoning on a mobile robot about its dynamic, partially known environment may differ substantially from that in knowledge-based pure software systems, where most of the named successes have been registered. Moreover, recent knowledge about the robot’s environment cannot be given a priori, but needs to be updated from sensor data, involving challenging problems of symbol grounding and knowledge base change. This chapter sketches the main robotics relevant topics of symbol-based AI reasoning. Basic methods of knowledge representation and inference are described in general, covering both logic and probability-based approaches. The chapter first gives a motivation by example, to what extent symbolic reasoning has the potential of helping robots perform in the first place. Then (Sect. 14.2), we sketch the landscape of representation languages available for the endeavor. After that (Sect. 14.3), we present approaches and results for several types of practical, robotics-related reasoning tasks, with an emphasis on temporal and spatial reasoning. Plan-based robot control is described in some more detail in Sect. 14.4. Section 14.5 concludes.

Place, publisher, year, edition, pages
Springer, 2016, 2. p. 329-356
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-45482ISBN: 978-3-319-32552-1 (print)OAI: oai:DiVA.org:oru-45482DiVA, id: diva2:844581
Available from: 2015-08-06 Created: 2015-08-06 Last updated: 2018-01-11Bibliographically approved

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Pecora, Federico

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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
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More languages
Output format
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