kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
Creating Trustworthy AI for UAS using Labeled Backchained Behavior Trees
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0002-7714-928X
Saab Aeronautics, Sweden.
2023 (English)In: 2023 International Conference on Unmanned Aircraft Systems, ICUAS 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 1029-1036Conference paper, Published paper (Refereed)
Abstract [en]

Unmanned Aerial Systems (UAS) have the potential to provide cost effective solutions to many problems, but their control systems need to be safe and trustworthy in order to realize this potential. In this paper we show how behavior trees (BTs), created using backward chaining and using a particular way of labelling subtrees, can be used to meet the requirements of trustworthy autonomy described in a US air force (USAF) report. Behavior Trees represent a modular, reactive and transparent way of structuring a control system that is receiving increasing interest in the UAS community. While their safety and efficiency have been investigated in prior research, their connection to trustworthy autonomy has not been explored. A set of guidelines for trustworthy autonomy, taken from a USAF report, include items such as: being similar to how humans parse problems, being able to explain its reasoning in a concise way, and being able to be visualized at different levels of resolution. We propose a new way of deriving explanations that conform to these guidelines, using a particular labeling of subtrees in the BT combined with a structured design methodology called backward chaining. The proposed approach is illustrated in a detailed example.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2023. p. 1029-1036
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-335091DOI: 10.1109/ICUAS57906.2023.10156149ISI: 001032475700140Scopus ID: 2-s2.0-85165706707OAI: oai:DiVA.org:kth-335091DiVA, id: diva2:1793221
Conference
2023 International Conference on Unmanned Aircraft Systems, ICUAS 2023, Warsaw, Poland, Jun 6 2023 - Jun 9 2023
Note

Part of ISBN 9798350310375

QC 20230831

Available from: 2023-08-31 Created: 2023-08-31 Last updated: 2023-09-04Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Ögren, Petter

Search in DiVA

By author/editor
Ögren, Petter
By organisation
Robotics, Perception and Learning, RPL
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 77 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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