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Titel:

Human-Inspired Neurorobotic System for Classifying Surface Textures by Touch

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Friedl, Ken; Russell Voelker, Aaron; Peer, Angelika; Eliasmith, Chris
Abstract:
Giving robots the ability to classify surface textures requires appropriate sensors and algorithms. Inspired by the biology of human tactile perception, we implement a neurorobotic texture classifier with a recurrent spiking neural network, using a novel semi-supervised approach for classifying dynamic stimuli. Input to the network is supplied by accelerometers mounted on a robotic arm. The sensor data is encoded by a heterogeneous population of neurons, modeled to match the spiking activity of...     »
Stichworte:
neurorobotics, biologically-inspired robots, force and tactile sensing, sense of touch, spiking neural networks
Zeitschriftentitel:
IEEE Robotics and Automation Letters
Jahr:
2016
Volltext / DOI:
doi:10.1109/LRA.2016.2517213
Verlag / Institution:
IEEE
Semester:
WS 15-16
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