Abstract
Adaptability to various environments is needed for a robot that supports our lives. Environmental identification is important for a mobile robot that works in multiple environments (e.g., different rooms). We present an environmental modeling method based on state representation, which represents a change in sensory information. Our model enables the mobile robot to identify which environment it is in. The results of experiments on a real mobile robot with only low-sensitivity infrared sensors show the effectiveness of our method, and a comparison between our method and a conventional one shows that ours has higher performance.
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Gouko, M., Ito, K. (2010). Environmental Modeling and Identification Based on Changes in Sensory Information. In: Gavrilova, M.L., Tan, C.J.K. (eds) Transactions on Computational Science VIII. Lecture Notes in Computer Science, vol 6260. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16236-7_1
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DOI: https://doi.org/10.1007/978-3-642-16236-7_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16235-0
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