Abstract
In an agent system that needs to operate in a real world, the problem of maintaining a consistent world model in the face of unreliable, incomplete and inconsistent sensory data should be solved. In this paper, we present an approach that addresses this problem by applying an argumentation-based scene interpretation framework for accurately modelling and representing the observations and beliefs of an agent. Our approach is based on temporal and probabilistic defeasible logic programming for reasoning. The performance of our approach is evaluated on simulation experiments in the Stage Robot Simulator. We also show that our approach is applicable to real world scenarios with an autonomous Pioneer 3-AT robot.
Original language | English |
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Title of host publication | Proceedings of the 17th International Conference on Advanced Robotics, ICAR 2015 |
Editors | Uluc Saranli, Sinan Kalkan |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 649-654 |
Number of pages | 6 |
ISBN (Electronic) | 9781467375092 |
DOIs | |
Publication status | Published - 13 Oct 2015 |
Event | 17th International Conference on Advanced Robotics, ICAR 2015 - Istanbul, Turkey Duration: 27 Jul 2015 → 31 Jul 2015 |
Publication series
Name | Proceedings of the 17th International Conference on Advanced Robotics, ICAR 2015 |
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Conference
Conference | 17th International Conference on Advanced Robotics, ICAR 2015 |
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Country/Territory | Turkey |
City | Istanbul |
Period | 27/07/15 → 31/07/15 |
Bibliographical note
Publisher Copyright:© 2015 IEEE.