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Integrating robot task planner with common-sense knowledge base to improve the efficiency of planning

  • Renxi Qiu
    ,
  • Ahmed Al-Moadhen
    ,
  • Michael Packianather
    ,
  • Ze Ji
    ,
  • Rossi Setchi
  • Cardiff University
Research Output: Contribution to journal Article Peer-review

Abstract

This paper presents a developed approach for intelligently generating symbolic plans by mobile robots acting in domestic environments, such as offices and houses. The significance of the approach lies in developing a new framework that consists of the new modeling of high-level robot actions and then their integration with common-sense knowledge in order to support a robotic task planner. This framework will enable interactions between the task planner and the semantic knowledge base directly. By using common-sense domain knowledge, the task planner will take into consideration the properties and relations of objects and places in its environment, before creating semantically related actions that will represent a plan. This plan will accomplish the user order. The robot task planner will use the available domain knowledge to check the next related actions to the current one and the action's conditions met will be chosen. Then the robot will use the immediately available knowledge information to check whether the plan outcomes are met or violated.

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 211-220

Journal (Volume, Issue Number)

Procedia Computer Science (Volume 22)

Publication milestones

  • Published - 01/01/2013

Publication status

Published - 01/01/2013

ISSN

1877-0509

External Publication IDs

  • handle.net: 10547/336232
  • Scopus: 84896971021

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