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Combining Task and Motion Planning: Challenges and Guidelines
Intelligent Robotics Lab, School of Computer Science, University of Birmingham, Birmingham, United Kingdom.ORCID iD: 0000-0002-4527-7586
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-9652-7864
Knowledge-Based Systems Group, TU Wien, Vienna, Austria.
2021 (English)In: Frontiers in Robotics and AI, E-ISSN 2296-9144, Vol. 8, article id 637888Article in journal (Refereed) Published
Abstract [en]

Combined Task and Motion Planning (TAMP) is an area where no one-fits-all solution can exist. Many aspects of the domain, as well as operational requirements, have an effect on how algorithms and representations are designed. Frequently, trade-offs have to be madet o build a system that is effective. We propose five research questions that we believe need to be answered to solve real-world problems that involve combined TAMP. We show which decisions and trade-offs should be made with respect to these research questions, and illustrate these on examples of existing application domains. By doing so, this article aims to provide a guideline for designing combined TAMP solutions that are adequate and effective in the target scenario.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2021. Vol. 8, article id 637888
Keywords [en]
Task and motion planning, integrative AI, knowledge representation, automated reasoning, industrial applications of robotics
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-91851DOI: 10.3389/frobt.2021.637888ISI: 000656841700001PubMedID: 34095239Scopus ID: 2-s2.0-85107191930OAI: oai:DiVA.org:oru-91851DiVA, id: diva2:1555589
Funder
Knowledge FoundationVinnovaEU, Horizon 2020, 825619Available from: 2021-05-19 Created: 2021-05-19 Last updated: 2021-06-21Bibliographically approved

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Pecora, Federico

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