DocumentCode :
1714355
Title :
High performance DT-CNN camera device design on ACTEL IGLOO low power FPGA
Author :
Consul-Pacareu, S. ; Albo-Canals, J. ; Vilasís-Cardona, X. ; Riera-Baburés, J.
Author_Institution :
LIFAELS, La Salle-Ramon Llull Univ., Barcelona, Spain
fYear :
2011
Firstpage :
37
Lastpage :
40
Abstract :
In this paper we present a complete study on the balance between high performance image processing and low power consumption without using expensive components. Our proposal consists in implementing a Discrete Time Cellular Neural Network (DT-CNN) on a low power Actel IGLOO nano Field Programmable Gate Array (FPGA). This is a definitive step further from previous work to obtain an intelligent camera device for robots. Applications in Robot Guidance have rapidly increased in the last years as robots break in different fields of everyday live, which most of this robotic devices need sensors for navigation. Our proposed low cost solution avoids highly complex architectures, expensive smart sensors and low performance navigation systems.
Keywords :
cameras; cellular neural nets; discrete time systems; field programmable gate arrays; intelligent sensors; logic design; low-power electronics; nanotechnology; navigation; ACTEL IGLOO low power FPGA; DT-CNN camera device design; discrete time cellular neural network; expensive components; high performance image processing; intelligent camera robot device; low performance navigation systems; low power Actel IGLOO nano field programmable gate array; low power consumption; robot guidance; robotic devices; smart sensors; Cameras; Computational modeling; Field programmable gate arrays; Power demand; Random access memory; Robot sensing systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuit Theory and Design (ECCTD), 2011 20th European Conference on
Conference_Location :
Linkoping
Print_ISBN :
978-1-4577-0617-2
Electronic_ISBN :
978-1-4577-0616-5
Type :
conf
DOI :
10.1109/ECCTD.2011.6043338
Filename :
6043338
Link To Document :
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