Abstract
A generic cognitive robotics framework should integrate multimodalities to preserve consistency, minimize uncertainty, and adopt human like concepts in order to achieve efficient interaction with the operator. Fusion is the process of combining observations, knowledge, and data from multiple sensors into a single and coherent percept. There are several data fusion architectures existing in the literature, nevertheless, a complete and unified architecture for data fusion is not in the picture yet. In this paper, we present a new data fusion architecture pursuing the same goal of realizing such generalized architecture initiated by JDL (Joint Director’s of Laboratories). The proposed architecture comprises two degrees of freedom represented by three levels of abstractions, and four layers of situation awareness. We also suggest incorporating a cognitive memory model that best suits our targeted robotics applications.
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Baklouti, M., AbouSaleh, J., Khaledgi, B., Karray, F. (2009). Towards a Comprehensive Data Fusion Architecture For Cognitive Robotics. In: Damiani, E., Jeong, J., Howlett, R.J., Jain, L.C. (eds) New Directions in Intelligent Interactive Multimedia Systems and Services - 2. Studies in Computational Intelligence, vol 226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02937-0_13
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DOI: https://doi.org/10.1007/978-3-642-02937-0_13
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