Abstract
This paper considers the robot navigation task as an algorithmic and representational one in a way that the performance of the navigation task cannot be measured without combining those two elements. As a result of this view, a unique new navigation strategy based on combined multi-fusion planning algorithms and multi-paradigm representation schemes is presented. An overall architecture for a new navigation strategy is also proposed. Discrete and continuous planning algorithms are combined in a hierarchal fashion. GIS models and ontology are also combined to form rich media for representing dynamic data and knowledge. Experimental results with an evaluation of the schemes are presented.
Original language | English |
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Pages (from-to) | 133-142 |
Number of pages | 10 |
Journal | Robotics and Autonomous Systems |
Volume | 96 |
Early online date | 1 Aug 2017 |
DOIs | |
Publication status | Published - Oct 2017 |
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Matthew Walter Dunnigan
- School of Engineering & Physical Sciences - Associate Professor
- School of Engineering & Physical Sciences, Institute of Sensors, Signals & Systems - Associate Professor
Person: Academic (Research & Teaching)