All Publications

NeoN: Neuromorphic Control System for Autonomous Robotic Navigation

Grant Bruer, Parker Mitchell, Trevor Sharpe, Andrew Valesky, David Young, and Mark E. Dean

April, 2017

University of Tennessee ECE402/CS402 Senior Design Final Project Report

-

View Article

Abstract

The goal of this senior design project was to demonstrate the power and efficiency of the neuromorphic architecture by producing a robot that roamed in a pseudorandom manner following the path of least resistance and avoided obstacles in its environment. The robot was required to use a track system for propulsion and a sweeping Garmin LIDAR-Lite v3 sensor on a servo for observing its environment. The trained neural network was implemented on a Digilent Genesys 2 field-programmable gate array (FPGA) board with a MicroBlaze processor core.

Citation Information

Text


author          G. Bruer and J. P. Mitchell and T. Sharpe and A. Valesky and 
                D. Young and M. E. Dean
title           {NeoN}: Neuromorphic Control System for Autonomous Robotic Navigation
howpublished    University of Tennessee ECE402/CS402 Senior Design Final Project Report
year            2017

Bibtex


@MISC{bms:17:nnc,
    author = "G. Bruer and J. P. Mitchell and T. Sharpe and A. Valesky and D. Young and M. E. Dean",
    title = "{NeoN}: Neuromorphic Control System for Autonomous Robotic Navigation",
    howpublished = "University of Tennessee ECE402/CS402 Senior Design Final Project Report",
    year = "2017"
}