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Title:
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ADAPTIVE WEIGHTED AVERAGE SENSOR FUSION ALGORITHMS FOR MOBILE ROBOTS |
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Author(s):
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Keren Kapach , Yael Edan |
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ISBN:
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978-972-8924-39-3 |
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Editors:
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António Palma dos Reis, Katherine Blashki and Yingcai Xiao (series editors:Piet Kommers, Pedro Isaías and Nian-Shing Chen) |
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Year:
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2007 |
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Edition:
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Single |
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Keywords:
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sensor fusion, algorithms, robotics and autonomous mobile robots. |
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Type:
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Full Paper |
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First Page:
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43 |
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Last Page:
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50 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This paper presents a new set of sensor fusion algorithms for mapping the environment of mobile robots using grid maps.
The algorithms use the adaptive weighted average method and consider as weights the number of times each cell was
sampled by the sensor. Analysis in an indoor mobile robot experiment indicated superior performance of one of the new
algorithms when compared to a previously developed adaptive fuzzy logic algorithm. |
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