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Document type:
Zeitschriftenaufsatz 
Author(s):
Friedl, K., Voelker, E., Russel, A., Peer, A., Eliasmith, C. 
Title:
Human-Inspired Neurorobotic System for Classifying Surface Textures by Touch 
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...    »
 
Keywords:
neurorobotics, biologically-inspired robots, force and tactile sensing, sense of touch, spiking neural networks 
Journal title:
IEEE Robotics and Automation Letters 
Year:
2016 
Publisher:
IEEE 
Semester:
WS 15-16