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Towards Blended Reactive Planning and Acting using Behavior Trees
Istituto Italiano di Tecnologia - IIT, Genoa, Italy.ORCID iD: 0000-0003-0289-7424
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.ORCID iD: 0000-0002-7714-928X
2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we show how a planning algorithm can be used to automatically create and update a Behavior Tree (BT), controlling a robot in a dynamic environment. The planning part of the algorithm is based on the idea of back chaining. Starting from a goal condition we iteratively select actions to achieve that goal, and if those actions have unmet preconditions, they are extended with actions to achieve them in the same way. The fact that BTs are inherently modular and reactive makes the proposed solution blend acting and planning in a way that enables the robot to effectively react to external disturbances. If an external agent undoes an action the robot re- executes it without re-planning, and if an external agent helps the robot, it skips the corresponding actions, again without re- planning. We illustrate our approach in two different robotics scenarios.

Place, publisher, year, edition, pages
IEEE Robotics and Automation Society, 2019.
National Category
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-248671OAI: oai:DiVA.org:kth-248671DiVA, id: diva2:1303467
Conference
2019 IEEE International Conference on Robotics and Automation (ICRA)
Funder
Swedish Foundation for Strategic Research , IRC15-0046EU, Horizon 2020, 644938
Note

QC 20190429

Available from: 2019-04-09 Created: 2019-04-09 Last updated: 2019-04-29Bibliographically approved

Open Access in DiVA

fulltext(624 kB)16 downloads
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
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  • Other locale
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Output format
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