Krauhausen Imke, Koutsouras Dimitrios A, Melianas Armantas, Keene Scott T, Lieberth Katharina, Ledanseur Hadrien, Sheelamanthula Rajendar, Giovannitti Alexander, Torricelli Fabrizio, Mcculloch Iain, Blom Paul W M, Salleo Alberto, van de Burgt Yoeri, Gkoupidenis Paschalis
Max Planck Institute for Polymer Research, Mainz, Germany.
Microsystems, Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, Netherlands.
Sci Adv. 2021 Dec 10;7(50):eabl5068. doi: 10.1126/sciadv.abl5068.
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.
在生物体内，感觉和运动过程是分布式的，局部融合的，并且能够形成动态的感觉运动关联。我们为放置在迷宫中的机器人引入了一种简单高效的有机神经形态电路，用于局部感觉运动融合和处理。当机器人受到外部环境刺激时，视觉运动关联在可适应的神经形态电路上形成。通过这种片上感觉运动集成，机器人在视觉指示路径的引导下，学会沿着通往迷宫出口的路径行进。有机神经形态电子器件易于加工的特性及其非常规的外形尺寸，与教育用途的机器人技术相结合，展示了一种有前景的方法，即通过分散式感觉运动集成，构建一个价格实惠、多功能且易于使用的平台，用于探索、设计和评估行为智能。
