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An adaptive appearance-based map for long-term topological localization of mobile robots

By Feras Dayoub and Tom Duckett


This work considers a mobile service robot which uses an appearance-based representation of its workplace as a map, where the current view and the map are used to estimate the current position in the environment. Due to the nature of real-world environments such as houses and offices, where the appearance keeps changing, the internal representation may become out of date after some time. To solve this problem the robot needs to be able to adapt its internal representation continually to the changes in the environment. This paper presents a method for creating an adaptive map for long-term appearance-based localization of a mobile robot using long-term and short-term memory concepts, with omni-directional vision as the external sensor

Topics: G700 Artificial Intelligence, G400 Computer Science, G760 Machine Learning, G740 Computer Vision
Publisher: IEEE
Year: 2008
DOI identifier: 10.1109/IROS.2008.4650701
OAI identifier: oai:eprints.lincoln.ac.uk:1679

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