Abstract
The ease and efficiency with which biological systems deal with several real world problems, that have been persistently challenging to implement in artificial systems, is a key motivation in biomimetic robotics. In interacting with its environment, the first challenge any agent faces is to extract meaningful patterns in the inputs from its sensors. This problem of pattern recognition has been characterized as an inference problem in cortical computation. The work presented here implements the hierarchical temporal memory (HTM) model of cortical computation using inputs from an array of artificial tactile sensors to recognize simple Braille patterns. Although the current work has been implemented using a small array of robot whiskers, the architecture can be extended to larger arrays of sensors of any arbitrary modality.
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Motiwala, A., Fox, C.W., Lepora, N.F., Prescott, T.J. (2011). Sensing with Artificial Tactile Sensors: An Investigation of Spatio-temporal Inference. In: Groß, R., Alboul, L., Melhuish, C., Witkowski, M., Prescott, T.J., Penders, J. (eds) Towards Autonomous Robotic Systems. TAROS 2011. Lecture Notes in Computer Science(), vol 6856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23232-9_23
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DOI: https://doi.org/10.1007/978-3-642-23232-9_23
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