3,377 research outputs found

    Spike-based control monitoring and analysis with Address Event Representation

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    Neuromorphic engineering tries to mimic biological information processing. Address-Event Representation (AER) is a neuromorphic communication protocol for spiking neurons between different chips. We present a new way to drive robotic platforms using spiking neurons. We have simulated spiking control models for DC motors, and developed a mobile robot (Eddie) controlled only by spikes. We apply AER to the robot control, monitoring and measuring the spike activity inside the robot. The mobile robot is controlled by the AER-Robot tool, and the AER information is sent to a PC using the USBAERmini2 interface.Junta de Andalucía P06-TIC-01417Ministerio de Educación y Ciencia TEC2006-11730-C03-0

    Neuro-inspired system for real-time vision sensor tilt correction

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    Neuromorphic engineering tries to mimic biological information processing. Address-Event-Representation (AER) is an asynchronous protocol for transferring the information of spiking neuro-inspired systems. Currently AER systems are able sense visual and auditory stimulus, to process information, to learn, to control robots, etc. In this paper we present an AER based layer able to correct in real time the tilt of an AER vision sensor, using a high speed algorithmic mapping layer. A codesign platform (the AER-Robot platform), with a Xilinx Spartan 3 FPGA and an 8051 USB microcontroller, has been used to implement the system. Testing it with the help of the USBAERmini2 board and the jAER software.Junta de Andalucía P06-TIC-01417Ministerio de Educación y Ciencia TEC2006-11730-C03-02Ministerio de Ciencia e Innovación TEC2009-10639-C04-0

    On Real-Time AER 2-D Convolutions Hardware for Neuromorphic Spike-Based Cortical Processing

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    In this paper, a chip that performs real-time image convolutions with programmable kernels of arbitrary shape is presented. The chip is a first experimental prototype of reduced size to validate the implemented circuits and system level techniques. The convolution processing is based on the address–event-representation (AER) technique, which is a spike-based biologically inspired image and video representation technique that favors communication bandwidth for pixels with more information. As a first test prototype, a pixel array of 16x16 has been implemented with programmable kernel size of up to 16x16. The chip has been fabricated in a standard 0.35- m complimentary metal–oxide–semiconductor (CMOS) process. The technique also allows to process larger size images by assembling 2-D arrays of such chips. Pixel operation exploits low-power mixed analog–digital circuit techniques. Because of the low currents involved (down to nanoamperes or even picoamperes), an important amount of pixel area is devoted to mismatch calibration. The rest of the chip uses digital circuit techniques, both synchronous and asynchronous. The fabricated chip has been thoroughly tested, both at the pixel level and at the system level. Specific computer interfaces have been developed for generating AER streams from conventional computers and feeding them as inputs to the convolution chip, and for grabbing AER streams coming out of the convolution chip and storing and analyzing them on computers. Extensive experimental results are provided. At the end of this paper, we provide discussions and results on scaling up the approach for larger pixel arrays and multilayer cortical AER systems.Commission of the European Communities IST-2001-34124 (CAVIAR)Commission of the European Communities 216777 (NABAB)Ministerio de Educación y Ciencia TIC-2000-0406-P4Ministerio de Educación y Ciencia TIC-2003-08164-C03-01Ministerio de Educación y Ciencia TEC2006-11730-C03-01Junta de Andalucía TIC-141
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