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