Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Field interactive robotic entity (FIRE) adaptive learning of environment using neural networks a VLSI implementation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Chandramouli, K. ; SRM Inst. of Sci. & Technol., Kattankulathur, India ; Sankarshanan, B.

Field interactive robotic entity (FIRE) is an ATMEL™ micro controller controlled (belong to the 8051 microcontroller) robot. The maneuvering capabilities of the robot are based on two sensors, touch and edge detector. The touch sensor is a switch, to produce a low signal when an obstacle is encountered. The limitation of the robot is that it can sense an obstacle only when it makes a contact with it. To overcome this limitation an application specific integrated circuit [ASIC] chip is proposed incorporating neural networks. The learning algorithm implemented is 'unsupervised learning' based on memory. The proposed design is aimed at implementing in an XILINX™ Spartan FPGA.

Published in:

Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on  (Volume:1 )

Date of Conference:

31 Aug.-4 Sept. 2004