In living organisms, sensory and motor processes are distributed, locally merged, and capable of forming dynamic sensorimotor associations. We introduce a simple and efficient organic neuromorphic circuit for local sensorimotor merging and processing on a robot that is placed in a maze. While the robot is exposed to external environmental stimuli, visuomotor associations are formed on the adaptable neuromorphic circuit. With this on-chip sensorimotor integration, the robot learns to follow a path to the exit of a maze, while being guided by visually indicated paths. The ease of processability of organic neuromorphic electronics and their unconventional form factors, in combination with education-purpose robotics, showcase a promising approach of an affordable, versatile, and readily accessible platform for exploring, designing, and evaluating behavioral intelligence through decentralized sensorimotor integration.


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    Titel :

    Organic neuromorphic electronics for sensorimotor integration and learning in robotics



    Erscheinungsdatum :

    2021-12-10


    Anmerkungen:

    Krauhausen , I , Koutsouras , D A , Melianas , A , Keene , S T , Lieberth , K , Ledanseur , H , Sheelamanthula , R , Giovannitti , A , Torricelli , F , Mcculloch , I , Blom , P W M , Salleo , A , van de Burgt , Y & Gkoupidenis , P 2021 , ' Organic neuromorphic electronics for sensorimotor integration and learning in robotics ' , Science Advances , vol. 7 , no. 50 , eabl5068 . https://doi.org/10.1126/sciadv.abl5068



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    DDC:    629



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