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# Brain used in conjunction with GAFindBlobNN.py to create a robot
# that chases after red objects.
# Network inputs: 8
# 4 virtual sonar sensors and 4 pieces of color blob info.
# Sonar values are the minimums of four groups:
# back, front-left, front-right, and front.
# The color blob info consists of the range to closest blob,
# and 3 nodes which code for direction of the closest blob:
# 100=left, 010=center, 001=right, and 000=none.
# All inputs are scaled between 0 and 1.
# Network outputs: 2
# Translate and rotate.
from pyrobot.brain import Brain
from pyrobot.brain.conx import *
from time import *
# The robot will get translate and rotate values in the range [-0.5,0.5],
# but the neural network will generate outputs in the range [0,1].
def toNetworkUnits(val):
return (val + 0.5)
def toRobotUnits(val):
return (val - 0.5)
class NNBrain(Brain):
def setup(self, **args):
self.net = Network()
self.net.addLayers(8,6,2)
self.net.setLearning(0)
if not self.robot.hasA("camera"):
# Assume Stage, which uses the BlobCamera:
self.robot.startDevice("BlobCamera")
self.robot.camera[0].addFilter("match", 255, 0, 0)
self.robot.camera[0].addFilter("blobify",0,255,255,0,1,1,1,)
self.robot.range.units = "meters"
self.robot.range.setMaxvalue(4.5) # about as far as sonar can see in room
self.robot.range.units = "scaled"
self.counter = 0
self.currentInputs = [0] * 8
def getBlobInfo(self, (x1, y1, x2, y2, pixels)):
blobLeft, blobCenter, blobRight = (0.0, 0.0, 0.0)
if (x1, y1, x2, y2) == (0.0, 0.0, 0.0, 0.0):
return 0.0, blobLeft, blobCenter, blobRight
# how close is the blob? how much of the view does it occupy?
blobRange = (y2 - y1) / float(self.robot.camera[0].height)
# where is the blob in the image?
center = (x2 + x1) / 2.0
# is it in the left third of view?
if center < self.robot.camera[0].width/3.0: # left third
blobLeft = 1.0
# right third?
elif center > 2.0 * self.robot.camera[0].width/3.0: # right third
blobRight = 1.0
# must be in center
else:
blobCenter = 1.0
return blobRange, blobLeft, blobCenter, blobRight
def getInputs(self):
# get minimum values for each area:
back = min([s.distance() for s in self.robot.range["back"]])
left = min([s.distance() for s in self.robot.range["front-left"]])
front = min([s.distance() for s in self.robot.range["front"]])
right = min([s.distance() for s in self.robot.range["front-right"]])
blobList = self.robot.camera[0].filterResults[1]
if blobList != []:
blobRange, blobLeft, blobCenter, blobRight = self.getBlobInfo(blobList[0]) # biggest blob
self.currentInputs = [back, left, front, right, blobRange, blobLeft, blobCenter, blobRight]
self.net['input'].copyActivations(self.currentInputs)
def getOutputs(self):
translate = toRobotUnits(self.net['output'].activation[0])
rotate = toRobotUnits(self.net['output'].activation[1])
return translate, rotate
def step(self):
print "adapter is stepping"
self.robot.update()
self.getInputs()
self.net.propagate()
translate, rotate = self.getOutputs()
self.move(translate, rotate)
self.counter += 1
def INIT(engine):
return NNBrain('NNBrain', engine) |
