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 |
|---|---|
| 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)