Towards automated task planning for service robots using semantic knowledge representation

Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902, Qiu, Renxi, Noyvirt, Alexandre Emilov, Soroka, Anthony John ORCID: https://orcid.org/0000-0002-9738-9352, Packianather, Michael Sylvester ORCID: https://orcid.org/0000-0002-9436-8206, Setchi, Rossitza ORCID: https://orcid.org/0000-0002-7207-6544, Li, D. and Xu, S. 2012. Towards automated task planning for service robots using semantic knowledge representation. Presented at: 2012 10th IEEE International Conference on Industrial Informatics (INDIN), Beijing, China, 25-27 July 2012. INDIN2012: IEEE 10th International Conference on Industrial Informatics. Los Alamitos, CA: IEEE, pp. 1194-1201. 10.1109/INDIN.2012.6301131

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Abstract

Automated task planning for service robots faces great challenges in handling dynamic domestic environments. Classical methods in the Artificial Intelligence (AI) area mostly focus on relatively structured environments with fewer uncertainties. This work proposes a method to combine semantic knowledge representation with classical approaches in AI to build a flexible framework that can assist service robots in task planning at the high symbolic level. A semantic knowledge ontology is constructed for representing two main types of information: environmental description and robot primitive actions. Environmental knowledge is used to handle spatial uncertainties of particular objects. Primitive actions, which the robot can execute, are constructed based on a STRIPS-style structure, allowing a feasible solution (an action sequence) for a particular task to be created. With the Care-O-Bot (CoB) robot as the platform, we explain this work with a simple, but still challenging, scenario named “get a milk box”. A recursive back-trace search algorithm is introduced for task planning, where three main components are involved, namely primitive actions, world states, and mental actions. The feasibility of the work is demonstrated with the CoB in a simulated environment.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Engineering Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering
Publisher:	IEEE
ISBN:	9781467303125
Last Modified:	06 Jul 2023 10:17
URI:	https://orca.cardiff.ac.uk/id/eprint/38346

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