Embodied mental imagery in cognitive robots

DI NUOVO, Alessandro, MAROCCO, Davide, DI NUOVO, Santo and CANGELOSI, Angelo (2017). Embodied mental imagery in cognitive robots. In: Springer handbook of model-based science. Springer Handbooks . Cham, Springer, 619-639.

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Official URL: https://link.springer.com/chapter/10.1007/978-3-31...
Link to published version:: https://doi.org/10.1007/978-3-319-30526-4_28
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The present chapter is focused on the exploitation of the concept of mental imagery as a fundamental cognitive capability to enhance the performance of cognitive robots. Indeed, the emphasis will be on the embodied imagery mechanisms applied to build artificial cognitive models of motor imagery and mental simulation to control complex behaviours of humanoid platforms, which represent the artificial body. With the aim of providing a panorama of the research activity on the topic, first we give an introduction on the Neuro-scientific and psychological background on mental imagery in order to help the reader to contextualize the multidisciplinary environment in which we operate. Then, we review the work done in the field of artificial cognitive systems and robotics to mimic the process behind the human ability of creating mental images of events and experiences, and to use this process as a cognitive mechanism to improve the behaviour of complex robots. Finally, we report the detail of three recent empirical studies in which mental imagery approaches were modelled trough artificial neural networks to enable a cognitive robot with some human-like capabilities. These empirical studies exemplify how the proprioceptive information can be used by mental imagery models to enhance the performance of the robot, giving evidence of the embodied cognition theories in the context of artificial cognitive systems.

Item Type: Book Section
Research Institute, Centre or Group - Does NOT include content added after October 2018: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Identification Number: https://doi.org/10.1007/978-3-319-30526-4_28
Page Range: 619-639
Depositing User: Alessandro Di Nuovo
Date Deposited: 14 Dec 2017 14:50
Last Modified: 18 Mar 2021 17:00
URI: https://shura.shu.ac.uk/id/eprint/17049

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