Abstract
In this paper, we analyze work on mobile robotics with the goal of highlighting the uses of contextual knowledge aiming at a flexible and robust performance of the system. In particular, we analyze different robotic tasks, ranging from robot behavior to perception, and then propose to characterize “contextualization” as a design pattern. As a result, we argue that many different tasks indeed can exploit contextual information and, therefore, a single explicit representation of knowledge about context may lead to significant advantages both in the design and in the performance of mobile robots.
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Calisi, D. et al. (2007). Uses of Contextual Knowledge in Mobile Robots. In: Basili, R., Pazienza, M.T. (eds) AI*IA 2007: Artificial Intelligence and Human-Oriented Computing. AI*IA 2007. Lecture Notes in Computer Science(), vol 4733. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74782-6_47
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DOI: https://doi.org/10.1007/978-3-540-74782-6_47
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