Diagnostic Reasoning for Robotics Using Action Languages

Erdem, Esra; Patoglu, Volkan; Saribatur, Zeynep G.

doi:10.1007/978-3-319-23264-5_27

Record link:

https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:3-3093
http://hdl.handle.net/20.500.12708/361

Title:

Diagnostic Reasoning for Robotics Using Action Languages

Citation:

Erdem, E., Patoglu, V., & Saribatur, Z. G. (2015). Diagnostic Reasoning for Robotics Using Action Languages. In F. Calimeri, G. Ianni, & M. Truszczynski (Eds.), Logic Programming and Nonmonotonic Reasoning : 13th International Conference, LPNMR 2015, Lexington, KY, USA, September 27-30, 2015. Proceedings (pp. 317–331). Switzerland. https://doi.org/10.1007/978-3-319-23264-5_27

CatalogPlus:

AC11362691

Publisher DOI:

10.1007/978-3-319-23264-5_27

Publication Type:

Inproceedings - Full-Paper Contribution

Language:

English

Authors:

Erdem, Esra
Patoglu, Volkan
Saribatur, Zeynep G.

Organisational Unit:

E192-02 - Forschungsbereich Databases and Artificial Intelligence

Published in:

Logic Programming and Nonmonotonic Reasoning : 13th International Conference, LPNMR 2015, Lexington, KY, USA, September 27-30, 2015. Proceedings

ISBN:

9783319232638

Volume:

9345

DOI of the book:

10.1007/978-3-319-23264-5

Date (published):

2015

Event name:

LPNMR: International Conference on Logic Programming and Nonmonotonic Reasoning 2015

Event date:

27-Sep-2015 - 30-Sep-2015

Event place:

Lexington, United States of America (the)

Number of Pages:

Publisher:

Switzerland

Publisher:

Springer, Cham

Keywords:

Diagnostic reasoning; Action languages; Answer set programming

Abstract:

We introduce a novel diagnostic reasoning method for robotic systems with multiple robots, to find the causes of observed discrepancies relevant for plan execution. Our method proposes (i) a systematic modification of the robotic action domain description by utilizing defaults, and (ii) algorithms to compute a smallest set of diagnoses (e.g., broken robots) by means of hypothetical reasoning over the modified formalism. The proposed method is applied over various robotic scenarios in cognitive factories.

Project (external):

TUBITAK Grant
TUBITAK Grant
TUBITAK Grant

Project ID:

111E116
113M422
114E491

Additional information:

The final publication is available via <a href="https://doi.org/10.1007/978-3-319-23264-5_27" target="_blank">https://doi.org/10.1007/978-3-319-23264-5_27</a>.

License:

In Copyright

Appears in Collections:

Conference Paper