oru.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Planning domain + execution semantics: a way towards robust execution?
Örebro University, School of Science and Technology. (AASS)
Osnabrück University, Osnabrück, Germany.
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-9652-7864
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0001-8229-1363
2014 (English)In: Qualitative Representations for Robots: Papers from the AAAI Spring Symposium, AAAI Press , 2014Conference paper, Published paper (Refereed)
Abstract [en]

Robots are expected to carry out complex plans in real world environments. This requires the robot to track the progress of plan execution and detect failures which may occur. Planners use very abstract world models to generate plans. Additional causal, temporal, categorical knowledge about the execution, which is not included in the planner's model, is often available. Can we use this knowledge to increase robustness of execution and provide early failure detection? We propose to use a dedicated Execution Model to monitor the executed plan based on runtime observations and rich execution knowledge. We show that the combined used of causal, temporal and categorical knowledge allows the robot to detect failures even when the effects of actions are not directly observable. A dedicated Execution model also introduces a degree of modularity, since the platform- and execution-specific knowledge does not need to be encoded into the planner.

Place, publisher, year, edition, pages
AAAI Press , 2014.
Series
Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence, ISSN 2159-5399
Keywords [en]
Semantic Execution Monitoring, Execution Monitoring, Lifted Planning, Hybrid Reasoning, HTN
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-33291OAI: oai:DiVA.org:oru-33291DiVA, id: diva2:690836
Conference
AAAI Spring Symposium
Projects
EU FP7 Project RACE
Funder
EU, FP7, Seventh Framework ProgrammeAvailable from: 2014-01-24 Created: 2014-01-24 Last updated: 2019-10-01Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Proceedings

Authority records BETA

Konečný, ŠtefanPecora, FedericoSaffiotti, Alessandro

Search in DiVA

By author/editor
Konečný, ŠtefanPecora, FedericoSaffiotti, Alessandro
By organisation
School of Science and Technology
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 541 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf