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Neural Information Processing: 21st International Conference, ICONIP 2014, Kuching, Malaysia, November 3-6, 2014. Proceedings, Part IIINeuromorphic hardware and cognitive robots seem like an obvious fit,
yet progress to date has been frustrated by a lack of tangible progress in achieving
useful real-world behaviour. System limitations: the simple and usually proprietary
nature of neuromorphic and robotic platforms, have often been the fundamental
barrier. Here we present an integration of a mature “neuromimetic” chip,
SpiNNaker, with the humanoid iCub robot using a direct AER - address-event
representation - interface that overcomes the need for complex proprietary protocols
by sending information as UDP-encoded spikes over an Ethernet link. Using
an existing neural model devised for visual object selection, we enable the robot
to perform a real-world task: fixating attention upon a selected stimulus. Results
demonstrate the effectiveness of interface and model in being able to control the
robot towards stimulus-specific object selection. Using SpiNNaker as an embeddable
neuromorphic device illustrates the importance of two design features in a
prospective neurorobot: universal configurability that allows the chip to be conformed
to the requirements of the robot rather than the other way ’round, and stan-
dard interfaces that eliminate difficult low-level issues of connectors, cabling,
signal voltages, and protocols. While this study is only a building block towards
that goal, the iCub-SpiNNaker system demonstrates a path towards meaningful
behaviour in robots controlled by neural network chips
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