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Organic neuromorphic electronics for sensorimotor integration and learning in robotics.

Published version
Peer-reviewed

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Type

Article

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Abstract

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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Keywords

46 Information and Computing Sciences, 40 Engineering, 4602 Artificial Intelligence

Journal Title

Sci Adv

Conference Name

Journal ISSN

2375-2548
2375-2548

Volume Title

7

Publisher

American Association for the Advancement of Science (AAAS)