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# Evolve a robot that chases after a particular color. The only object
# of that color is another robot which is running a simple avoid obstacles
# brain. The evolving robot is called adapter, the other robot is called
# opponent.
from pyrobot.engine import Engine
from pyrobot.brain.ga import *
from pyrobot.brain.conx import *
from pyrobot.system.config import *
import time
import os
class chaseGA(GA):
def __init__(self, cnt, filename):
self.filename = filename
self.popsize = cnt
self.output = open(self.filename + ".fit", "w")
config = Configuration()
config.put("pyrobot", "gui", "tk") # or tty
self.adapter = Engine("Player6665",
"NNFindBlob",
"StageSimulator",
config = config,
worldfile = "chase.cfg")
self.opponent =Engine("Player6666",
"BBWander")
# Wait for them to get initialized
time.sleep(1)
# Create a dummy network to determine the genome length
n = Network()
n.addLayers(8,6,2)
g = n.arrayify()
# Initial genes will have values between -10 and 10.
GA.__init__(self,
Population( cnt, Gene, min = -10, max = 10, size = len(g),
elitePercent=0.1, verbose = 1),
mutationRate = 0.1,
crossoverRate = 0.2,
maxGeneration = 10,
verbose = 1)
# Fitness at each step is the product of the color blob's range,
# the blob's location, and the robot's speed. If no blob is
# visible or if the robot is blocked from moving, then its fitness
# is 0 for those steps.
def fitnessFunction(self, genePos):
total = 0
# Reset the robots back to their starting positions.
self.adapter.robot.simulation[0].setPose('GreenRobot',-0.575,-1.247,45)
self.opponent.robot.simulation[0].setPose('RedRobot',0.194,1.236, 315)
self.adapter.brain.net.unArrayify(self.pop.individuals[genePos].genotype)
time.sleep(1)
self.adapter.pleaseRun()
self.opponent.pleaseRun()
# inputs 0:Bsonar 1:Lsonar 2:Fsonar 3:Rsonar
# 4:blobRange 5:blobToLeft 6:blobCentered 7:blobToRight
location = 0
for i in range(250):
time.sleep(0.1) # allow the robot to move
inputs = self.adapter.brain.currentInputs
translate, rotate = self.adapter.brain.getOutputs()
if self.adapter.brain.robot.stall:
translate = 0
print "moving robot", translate, rotate
if inputs[0]>0.92 or inputs[1]>0.92 or inputs[2]>0.92 or inputs[3]>0.92:
notblocked = 0
else:
notblocked = 1
if inputs[6]:
location = 1.0
elif inputs[5] or inputs[7]:
location = 0.5
else:
location = 0
current = notblocked * abs(translate) * location * inputs[4]
#print current
total += current
self.adapter.pleaseStop()
self.opponent.pleaseStop()
self.output.write("Gene " + str(genePos) + " fitness " + str(total) + "\n")
#print "**** TOTAL FITNESS ****", total
return total
def isDone(self):
self.output.write("Generation " + str(self.generation) + "\n")
self.output.write("Average fitness " + str(self.pop.avgFitness) +"\n")
self.output.write("Best Fitness " + str(self.pop.bestMember.fitness) +"\n")
self.output.write("-------------------------------------------------\n")
self.adapter.brain.net.unArrayify(self.pop.bestMember)
name = self.filename + "-gen" + str(self.generation) + ".wts"
self.adapter.brain.net.saveWeightsToFile(name)
if self.generation >= self.maxGeneration:
self.adapter.shutdown()
self.opponent.shutdown()
self.output.close()
return 1
else:
return 0
ga = chaseGA(10, "try")
ga.evolve()
ga.adapter.shutdown()
ga.opponent.shutdown() |
