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Bio-inspired Robotics

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Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA,volume 82)

Abstract

The fields of artificial intelligence and bio-inspired robotics have proven to cross several other fields of expertise including Cognitive Neuroscience. Here, we review principles of interaction between a natural (or artificial) organism and the environment where it lives. Then we ask whether such structural coupling shapes the way it behaves. For instance, how the sensory processing of the external world controls actions, and finally, behavior? We remind the main sources of inspiration for bio-inspired robotics and relate them to currently active fields of research like Embodiment and Enaction. These latter concepts are illustrated by examples of recent researches on two main aspects: (i) bio-inspired algorithms processing sensory signals coming from the outer world and (ii) bio-inspired controllers based on human behavior and physiology. Finally, we include an example of a bio-inspired robot controller design based on the concepts here exposed.

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Notes

  1. 1.

    https://project.inria.fr/keops.

  2. 2.

    https://github.com/mjescobar/MODI.

  3. 3.

    Scenario with color cubes: raw visual input (https://youtu.be/dLpcimLrfkA); retina-based visual input (https://youtu.be/I9dhgVhbiVs). Scenario with textured cubes: raw visual input (https://youtu.be/xlW1cIa42ls); retina-based visual input (https://youtu.be/Y6eHLBWxPfg).

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Acknowledgements

This work was partially supported by ANR-CONICYT KEOPS (ANR-47); ECOS-CONICYT C13E06; FONDECYT Nro. 1140403, Nro. 1150638; AFOSR Grant Nro. FA9550-19-1-0002; UTFSM DGIP-Grant 231358; Millennium Institute ICM-P09-022-F; Basal Project FB0008. We would also like to thank Patricio Cerda for the simulations performed using MODI and V-REP platform described in Sect. 4.

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Escobar, MJ., Alexandre, F., Viéville, T., Palacios, A. (2022). Bio-inspired Robotics. In: Auat, F., Prieto, P., Fantoni, G. (eds) Rapid Roboting. Intelligent Systems, Control and Automation: Science and Engineering, vol 82. Springer, Cham. https://doi.org/10.1007/978-3-319-40003-7_8

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