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Towards automated task planning for service robots using semantic knowledge representation

  • Ze Ji
    ,
  • Renxi Qiu
    ,
  • Alex Noyvirt
    ,
  • Anthony Soroka
    ,
  • Michael Packianather
    ,
  • Rossi Setchi
  • Cardiff University
    ,
  • Shanghai University
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
 Peer-review

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.

Publication Information

Output type

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
 Peer-review

Original language

English

Publication milestones

  • Published - 13/09/2012

Publication status

Published - 13/09/2012

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

ISBN (Print)

9781467303125

ISBN (Electronic)

9781467303125

Publication IDs

  • handle.net: 10547/275682
  • Scopus: 84868232745

Host publication title

nan

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