Paper Info
Title
ED-Scorbot: A robotic test-bed framework for FPGA-based neuromorphic systems
Abstract
Neuromorphic engineering is a growing and promising discipline nowadays. Neuro-inspiration and brain understanding applied to solve engineering problems is boosting new architectures, solutions and products today. The biological brain and neural systems process information at relatively low speeds through small components, called neurons, and it is impressive how they connect each other to construct complex architectures to solve in a quasi-instantaneous way visual and audio processing tasks, object detection and tracking, target approximation, grasping..., etc., with very low power. Neuromorphs are beginning to be very promising for a new era in the development of new sensors, processors, robots and software systems that mimic these biological systems. The event-driven Scorbot (ED-Scorbot) is a robotic arm plus a set of FPGA / microcontroller's boards and a library of FPGA logic joined in a completely event-based framework (spike-based) from the sensors to the actuators. It is located in Seville (University of Seville) and can be used remotely. Spike-based commands, through neuro-inspired motor controllers, can be sent to the robot after visual processing object detection and tracking for grasping or manipulation, after complex visual and audio-visual sensory fusion, or after performing a learning task. Thanks to the cascade FPGA architecture through the Address-Event-Representation (AER) bus, supported by specialized boards, resources for algorithms implementation are not limited.
Year
DOI
Venue
2016
10.1109/BIOROB.2016.7523630
2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)
Keywords
Field
DocType
ED-Scorbot,robotic test-bed framework,FPGA-based neuromorphic systems,neuromorphic engineering,biological brain,neural systems,event-driven Scorbot,robotic arm,FPGA,microcontroller boards,event-based framework,Seville,spike-based commands,neuro-inspired motor controllers,visual processing object detection,object tracking,audio-visual sensory fusion,learning task,cascade FPGA architecture,address-event-representation bus,AER
Object detection,Robotic arm,Visual processing,Computer science,Neuromorphic engineering,Field-programmable gate array,Software system,Robot,Audio signal processing,Embedded system
Conference
ISSN
ISBN
Citations 
2155-1782
978-1-5090-3288-4
0
PageRank 
References 
Authors
0.34
0
9
Name
Order
Citations
PageRank
F. Gomez-rodriguez132725.16
Angel Jiménez-fernandez29620.53
Fernando Perez-Peña3105.80
Lourdes Miro-Amarante400.34
M. Domínguez-Morales5388.21
a riosnavarro6417.36
Elena Cerezuela-Escudero7407.45
Daniel Cascado Caballero861.23
Alejandro Linares-barranco947353.18