This paper presents a bio-inspired approach for optical flow data interpretation based on fuzzy inference decision making for visual mobile robot navigation. The interpretation results of regionally averaged optical flow patterns with pyramid segmentation of the optical flow field deliver fuzzy topological and topographic information of the surrounding environment (topological structure from motion). It allows a topological localization in a global map as well as controlled locomotion (obstacle avoidance, goal seeking) in a changing and dynamic environment. The topological optical flow processing is embedded in a behavior based mobile robot navigation system which uses only a mono-camera as primary navigation sensor. The paper discusses the optical flow processing approach as well as the rule based fuzzy inference algorithms used. The implemented algorithms have been tested successfully with synthetic image data for a first verification and parameter tuning as well as in a real office environment with real image data.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:25194 |
| Date | 10 February 2010 |
| Creators | Mai, Ngoc Anh, Janschek, Klaus |
| Publisher | Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:article, info:eu-repo/semantics/article, doc-type:Text |
| Source | Proceedings of the RAAD 2009 18th International Workshop on Robotics in Alpe-Adria-Danube Region, May 25-27, 2009, Brasov, Romania, pp. 68-77 |
| Rights | info:eu-repo/semantics/openAccess |
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