Khandelwal, P, Yang, F, Leonetti, M et al. (2 more authors) (2014) Planning in action language BC while learning action costs for mobile robots. In: Chien, S, Fern, A, Ruml, A and Do, M, (eds.) Proceedings of the 24th International Conference on Automated Planning and Scheduling. ICAPS '14, 21-26 Jun 2014, Portsmouth, New Hampshire, USA. Association for the Advancement of Artificial Intelligence (AAAI) , pp. 472-480. ISBN 978-1-57735-660-8
Abstract
The action language BC provides an elegant way of formalizing dynamic domains which involve indirect effects of actions and recursively defined fluents. In complex robot task planning domains, it may be necessary for robots to plan with incomplete information, and reason about indirect or recursive action effects. In this paper, we demonstrate how BC can be used for robot task planning to solve these issues. Additionally, action costs are incorporated with planning to produce optimal plans, and we estimate these costs from experience making planning adaptive. This paper presents the first application of BC on a real robot in a realistic domain, which involves human-robot interaction for knowledge acquisition, optimal plan generation to minimize navigation time, and learning for adaptive planning.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2014, Association for the Advancement of Artificial Intelligence. This is an author produced version of a paper published in Procceedings of the 24th International Conference on Automated Planning and Scheduling. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Robotics; Answer Set Programming; Robot Task Planning |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence & Biological Systems (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 26 May 2016 15:51 |
Last Modified: | 17 Jan 2018 09:42 |
Published Version: | http://www.aaai.org/ocs/index.php/ICAPS/ICAPS14/pa... |
Status: | Published |
Publisher: | Association for the Advancement of Artificial Intelligence (AAAI) |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:97763 |