4.00
Hdl Handle:
http://hdl.handle.net/10547/275682
Title:
Towards automated task planning for service robots using semantic knowledge representation
Authors:
Ji, Ze; Qiu, Renxi; Noyvirt, Alex; Soroka, Anthony; Packianather, Michael; Setchi, Rossi; Li, Dayou; Xu, Shuo
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.
Affiliation:
Cardiff University; University of Bedfordshire; Shanghai University
Citation:
Ze Ji, Renxi Qiu, Noyvirt, A., Soroka, A., Packianather, M., Setchi, R., Dayou Li & Shuo Xu (2012) "Towards automated task planning for service robots using semantic knowledge representation", Industrial Informatics (INDIN), 2012 10th IEEE International Conference on, Industrial Informatics (INDIN), 2012 10th IEEE International Conference on,p1194-1201.
Publisher:
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date:
2012
URI:
http://hdl.handle.net/10547/275682
DOI:
10.1109/INDIN.2012.6301131
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6301131
Type:
Conference papers, meetings and proceedings
Language:
en
ISBN:
9781467303125
Appears in Collections:
Centre for Research in Distributed Technologies (CREDIT)

Full metadata record

DC FieldValue Language
dc.contributor.authorJi, Zeen_GB
dc.contributor.authorQiu, Renxien_GB
dc.contributor.authorNoyvirt, Alexen_GB
dc.contributor.authorSoroka, Anthonyen_GB
dc.contributor.authorPackianather, Michaelen_GB
dc.contributor.authorSetchi, Rossien_GB
dc.contributor.authorLi, Dayouen_GB
dc.contributor.authorXu, Shuoen_GB
dc.date.accessioned2013-03-22T13:55:47Z-
dc.date.available2013-03-22T13:55:47Z-
dc.date.issued2012-
dc.identifier.citationZe Ji, Renxi Qiu, Noyvirt, A., Soroka, A., Packianather, M., Setchi, R., Dayou Li & Shuo Xu (2012) "Towards automated task planning for service robots using semantic knowledge representation", Industrial Informatics (INDIN), 2012 10th IEEE International Conference on, Industrial Informatics (INDIN), 2012 10th IEEE International Conference on,p1194-1201.en_GB
dc.identifier.isbn9781467303125-
dc.identifier.doi10.1109/INDIN.2012.6301131-
dc.identifier.urihttp://hdl.handle.net/10547/275682-
dc.description.abstractAutomated 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.en_GB
dc.language.isoenen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_GB
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6301131en_GB
dc.subjectcontrol engineering computingen_GB
dc.subjectintelligent robotsen_GB
dc.subjectroboticsen_GB
dc.titleTowards automated task planning for service robots using semantic knowledge representationen
dc.typeConference papers, meetings and proceedingsen
dc.contributor.departmentCardiff Universityen_GB
dc.contributor.departmentUniversity of Bedfordshireen_GB
dc.contributor.departmentShanghai Universityen_GB
All Items in UOBREP are protected by copyright, with all rights reserved, unless otherwise indicated.