GitHub - NabilChouba/QTRobotAvoider: Robot is learning to avoid obstacles using neuronal network and backpropagation as learning algorithms

NabilChouba / QTRobotAvoider Public

Notifications You must be signed in to change notification settings
Fork 0
Star 1

Robot is learning to avoid obstacles using neuronal network and backpropagation as learning algorithms

Notifications

Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
Debug		Debug
doc		doc
FixedPoint.cpp		FixedPoint.cpp
FixedPoint.h		FixedPoint.h
FormCourbe.cpp		FormCourbe.cpp
FormCourbe.h		FormCourbe.h
Makefile		Makefile
VirtalFloat.H		VirtalFloat.H
VirtalFloat.cpp		VirtalFloat.cpp
confRobot.cpp		confRobot.cpp
confRobot.h		confRobot.h
confSigmoid.cpp		confSigmoid.cpp
confSigmoid.h		confSigmoid.h
connect.cpp		connect.cpp
connect.h		connect.h
default.txt		default.txt
drawlines.bsc		drawlines.bsc
drawlines.dsp		drawlines.dsp
drawlines.dsw		drawlines.dsw
drawlines.exe		drawlines.exe
drawlines.ncb		drawlines.ncb
drawlines.opt		drawlines.opt
drawlines.plg		drawlines.plg
drawlines.pro		drawlines.pro
enveronement.cpp		enveronement.cpp
enveronement.h		enveronement.h
f.exe		f.exe
frameChoitArth.cpp		frameChoitArth.cpp
frameChoitArth.h		frameChoitArth.h
imge.h		imge.h
mocFormCourbe.cpp		mocFormCourbe.cpp
mocconfRobot.cpp		mocconfRobot.cpp
mocconfSigmoid.cpp		mocconfSigmoid.cpp
mocconnect.cpp		mocconnect.cpp
mocframe.cpp		mocframe.cpp
net.cpp		net.cpp
net.h		net.h
network.cpp		network.cpp
network.h		network.h
obstacle.h		obstacle.h
qt-mt230nc.dll		qt-mt230nc.dll
readme.txt		readme.txt
robot.cpp		robot.cpp
robot.h		robot.h
save.txt		save.txt
save_Widget.txt		save_Widget.txt
save_WidgetMonStyle.txt		save_WidgetMonStyle.txt
save_Widget_18juite2005.txt		save_Widget_18juite2005.txt
save_Widgetc.txt		save_Widgetc.txt
save_obstacle.txt		save_obstacle.txt
sigmoid.cpp		sigmoid.cpp
sigmoid.h		sigmoid.h
vecteur.cpp		vecteur.cpp
vecteur.h		vecteur.h

Repository files navigation

idea is to create obstacles
try to avoid obstacles as if you are the robot
Neuronal network will use your way to learn how to do the same job
backpropagation is used as learning algorithm
ones ANN learn, you can see it on the field
the software is made in away to explore the effect of accuracy on backpropagation
you can any time switch configure the parameter of the arithmetic to use
fixed point or floating point and configure how many bit to be in use
a hardware FPGA - VHDL implementation will use the tool to determine the minimum precision needed
to reduce area overhead : and the Robot avoider is an example to validate the hardware.