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from pyrobot.brain import Brain
from pyrobot.brain import psom
import random
import time
def printList(ls, file):
for i in range(len(ls)):
file.write(str(ls[i]) + " ")
file.write("\n")
class BothSoms(Brain):
"""
Written by Cassandra Telenko and Lisa Meeden
This class is designed to work with the Pioneer simulated robot.
The goal of this class is to dynamically create a som of sonar data
from a robot doing simple navigation with obstacle avoidance.
It operates in two modes: CollectData and Run. The robot begins
in CollectData mode, and saves samples of its front sonar values
to a file called ir.dat while it is navigating. After a
designated number of steps (given by maxCollectSteps), the sample
data file is closed and used to initialize a som. Then the robot
goes into Run mode and uses its sonar values to train the som for
a designated number of steps (given by maxRunSteps).
With Doug and Deepak's avoidObstacles.
Modified By Cassandra Telenko:
It does the Above with Motor Values as well. The samples are saved to motor.dat.
"""
mode='CollectData'
maxSteps = 50
currStep = 0
minDistance = .9
sensorDat = open("ir.dat", "w")
sensorDat.write(str(8)+"\n")
motorDat = open("motor.dat","w")
motorDat.write(str(2)+"\n")
myMotorSom=1
mySensorSom=1
def step(self):
if self.mode=='CollectData':
if self.currStep<self.maxSteps:
instance=self.scout()
sensorinstance=instance[0]
motorinstance=instance[1]
printList(sensorinstance, self.sensorDat)
printList(motorinstance, self.motorDat)
self.currStep = self.currStep + 1
else:
self.sensorDat.close()
self.motorDat.close()
print "done collecting sample data"
self.stop() # stop the robot
#Initializes the Sensor Som
mySensorDat = psom.dataset(file="ir.dat")
self.mySensorSom = psom.psom(5,7,data=mySensorDat)
self.mySensorSom.init_training(0.02,3.0,self.maxSteps)
#Initializes the Motor Som
myMotorDat = psom.dataset(file="motor.dat")
self.myMotorSom = psom.psom(5,7,data=myMotorDat)
self.myMotorSom.init_training(0.02,3.0,self.maxSteps)
self.mode='RunSom'
self.currStep=0
print "done initializing"
elif self.mode=='RunSom':
instance=self.scout()
model1 = self.mySensorSom.train(psom.vector(instance[0]))
model2 = self.myMotorSom.train(psom.vector(instance[1]))
print "Sensor Input:\n" + str(instance[0]) + "\nSensor Model: "
model1.display()
print "Motor Input:\n" + str(instance[1]) + "\nMotor Model: "
model2.display()
self.currStep=self.currStep+1
if self.currStep==self.maxSteps:
self.mode='Done'
print "done training"
else:
self.stop() # stop the robot
def scout(self):
motorInstance=self.avoidObstacles()
time.sleep(0.25)
sensorInstance = range(0,8)
for i in range(0,8):
sensorInstance[i] = self.robot.sonar[0][i].value
return sensorInstance,motorInstance
def avoidObstacles(self):
minDist = self.minDistance
happy=random.random()
if min([s.value for s in self.robot.range["front"]]) < minDist:
if (random.random() < 0.5):
self.move(0, -happy)
return [0,-happy]
else:
self.move(0, happy)
return [0,happy]
elif min([s.value for s in self.robot.range["front-left"]]) < minDist:
self.move(0, -happy)
return [0,-happy]
elif min([s.value for s in self.robot.range["front-right"]]) < minDist:
self.move(0,happy)
return [0,happy]
else:
self.move(.2,0)
return [.2,0]
def INIT(engine):
return BothSoms('BothSoms', engine) |
