def Evolve(self):
self.parent = ROBOT()
self.parent.Evaluate(self.obstacles, playBlind=True, playPaused=False)
for g in range(0, c.NUM_GENERATIONS):
child = copy.deepcopy(self.parent)
child.Mutate()
child.Evaluate(self.obstacles, playBlind=True, playPaused=False)
printString = "[generation " + str(g) + " of " + str(
c.NUM_GENERATIONS) + "]: "
printString = printString + "[parent fitness: " + str(
self.parent.fitness) + "] "
printString = printString + "[child fitness: " + str(
child.fitness) + "] "
print printString
if (child.fitness > self.parent.fitness):
self.parent = child
class SIMULATION: def __init__(self,GUI,solutionID): self.solutionID = solutionID self.GUI = GUI self.physicsClient = p.connect(p.GUI if self.GUI else p.DIRECT) p.setAdditionalSearchPath(pybullet_data.getDataPath()) p.setGravity(0,0,-9.8) self.world = WORLD() self.robot = ROBOT(self.solutionID) def Get_Fitness(self): self.robot.Get_Fitness() def Run(self): for t in range(c.NUMBER_STEP): if self.GUI : time.sleep(1/240) p.stepSimulation() self.robot.Sense(t) self.robot.Think(t) self.robot.Act(t) def __del__(self): p.disconnect() '''
class SIMULATION:
def __init__(self, directOrGui, solutionID):
self.directOrGui = directOrGui
if self.directOrGui == "DIRECT":
self.physicsClient = p.connect(p.DIRECT)
elif self.directOrGui == "GUI":
self.physicsClient = p.connect(p.GUI)
p.setAdditionalSearchPath(pybullet_data.getDataPath())
p.setGravity(0, 0, -9.8)
self.world = WORLD()
self.robot = ROBOT(solutionID)
def Run(self):
for i in range(350):
p.stepSimulation()
self.robot.Sense(i)
self.robot.Think()
self.robot.Act(i)
if self.directOrGui == "GUI":
t.sleep(1 / 60)
def Get_Fitness(self, solutionID):
self.robot.Get_Fitness(solutionID)
def __del__(self):
p.disconnect()
def __init__(self, directOrGui, solutionID):
self.directOrGui = directOrGui
if self.directOrGui == "DIRECT":
self.physicsClient = p.connect(p.DIRECT)
elif self.directOrGui == "GUI":
self.physicsClient = p.connect(p.GUI)
p.setAdditionalSearchPath(pybullet_data.getDataPath())
p.setGravity(0, 0, -9.8)
self.world = WORLD()
self.robot = ROBOT(solutionID)
def __init__(self,GUI,solutionID): self.solutionID = solutionID self.GUI = GUI self.physicsClient = p.connect(p.GUI if self.GUI else p.DIRECT) p.setAdditionalSearchPath(pybullet_data.getDataPath()) p.setGravity(0,0,-9.8) self.world = WORLD() self.robot = ROBOT(self.solutionID)
def Start_Evaluation(self, env, pb, pp=False):
#---SIMULATOR---#
# start the simulator
self.sim = pyrosim.Simulator(eval_time=c.evalTime,
play_paused=pp,
play_blind=pb,
dt=c.discreteTime)
#---ROBOTS---#
# spawn bot
self.robot = ROBOT(self.sim, self.genome)
#---ENVIRONMENTS---#
env.Send_To(self.sim)
env.Send_Slope(self.sim)
#---SET COLLISIONS---#
# here we can assign collisions directly
# we can also make a predefined collision matrix
# using sim.create_collision_matrix(collision_type)
# where collision_type = 'all','none','inter' or 'intra'.
self.sim.assign_collision(self.robot, env)
#---SIMULATION---#
# start the simulation
self.sim.start()
def Start_Evaluation(self, pp, pb):
self.sim = PYROSIM(playPaused=pp, playBlind=pb, evalTime=500)
robot = ROBOT(self.sim, self.genome)
self.sim.Start()
def Start_Evaluation(self, env, pb=True, pp=True):
"""
Evaluates an individual over a simulation environment in pyrosim.
env: Pyrosim simulation env (object of ENVIRONMENT class)
play_blind : bool, optional
If True the simulation runs without graphics (headless) else if
False the simulation runs with graphics (the default is False)
play_paused : bool, optional
If True the simulation starts paused else if False the simulation
starts running. With simulation window in focus use Ctrl-p to
toggle pausing the simulation. (the default is False)
return:None
"""
self.sim = pyrosim.Simulator(eval_time=c.evalTime, play_blind=pb, play_paused=pp, xyz=[0, 7.5, 0.8], hpr=[270,0,0.0])
# add robot to sim
self.robot = ROBOT(self.sim,genome = self.genome, hidden_genome = self.hidden_genome, WHEEL_RADIUS = self.WHEEL_RADIUS, SPEED=self.SPEED, MASS=self.MASS)
# add environment to sim
env.Send_To(sim = self.sim)
# define collisions in sim
self.sim.assign_collision('ball', 'robot')
self.sim.assign_collision('goalpost', 'robot')
self.sim.assign_collision('ball', 'goalpost')
self.sim.start()
# retrieve the id of the ball position sensor
self.ball_psensor_id = env.ball_psensor_id
self.robot_position = self.robot.position
def Start_Evaluation(self, env, pp, pb):
self.sim = pyrosim.Simulator(play_paused=pp,
eval_time=c.evalTime,
play_blind=pb)
env.Send_To(self.sim)
self.robot = ROBOT(self.sim, self.genome)
self.sim.start()
def Evaluate(self):
sim = pyrosim.Simulator(play_paused=False, eval_time=100)
robot = ROBOT(sim, self.genome)
sim.start()
sim.wait_to_finish()
sensorData = sim.get_sensor_data(sensor_id=robot.P4, svi=1)
self.fitness = sensorData[-1]
def Start_Evaluation(self, pb):
self.sim = pyrosim.Simulator(
play_blind=pb,
play_paused=False,
eval_time=100)
self.robot = ROBOT(self.sim, self.genome)
self.sim.start()
def Start_Evaluation(self, hideSim=True, startPaused=False):
self.sim = PYROSIM(playPaused=startPaused,
playBlind=hideSim,
evalTime=c.evaluationTime)
robot = ROBOT(self.sim, self.genome)
self.sim.Start()
def Start_Evaluation(self, env, pp, pb):
self.sim = pyrosim.Simulator(play_paused=pp,
eval_steps=c.evalTime,
play_blind=pb)
env.Send_To(self.sim)
#self.sim.set_camera((-4, -1, 2), (15, -15, 0), tracking = 'none', body_to_track = 0)
self.robot = ROBOT(self.sim, self.genome)
self.sim.start()
def Start_Evaluation(self, pb, tower_y):
self.pb = pb
self.sim = pyrosim.Simulator( play_paused=True, eval_time=c.eval_time, play_blind=pb)
self.robot = ROBOT(self.sim, self.genome)
self.tower = TOWER(self.sim, tower_y)
self.sim.assign_collision("tower", "tower")
self.sim.assign_collision("tower", "robot")
self.sim.start()
def Evaluate(self, pb):
sim = pyrosim.Simulator(play_blind=pb)
robot = ROBOT(sim, self.genome)
sim.start()
sim.wait_to_finish()
x = sim.get_sensor_data(sensor_id=robot.P4, svi=0)
y = sim.get_sensor_data(sensor_id=robot.P4, svi=1)
z = sim.get_sensor_data(sensor_id=robot.P4, svi=2)
self.fitness = y[-1]
def Start_Evaluation(self, pb):
self.sim = pyrosim.Simulator(play_blind=pb,
eval_time=1000,
debug=False,
play_paused=False,
use_textures=True,
xyz=[-25, -50, 0])
self.robot = ROBOT(self.sim, self.genomehidden, self.genomeoutput)
self.sim.start()
def Start_Evaluation(self, env, pp, pb):
self.sim = PYROSIM(playPaused=pp,
playBlind=pb,
evalTime=constants.evaluationTime)
robot = ROBOT(self.sim, self.genome)
env.Send_To(self.sim)
self.sim.Start()
def Evaluate(self):
sim = pyrosim.Simulator(play_paused=False, eval_time=500)
robot = ROBOT(sim, random.random() * 2 - 1)
sim.start()
sim.wait_to_finish()
#gets x,y,z coord of individual's red cylinder.
y = sim.get_sensor_data(sensor_id=robot.P4, svi=1)
self.fitness = y[-1] #gets last element in y array (last y pos)
def Start_Evaluation(self, pb):
# starts simulation
self.sim = pyrosim.Simulator(play_paused=False,
eval_time=500,
play_blind=pb)
# call to function ROBOT which generates the scissor robot
self.robot = ROBOT(self.sim, self.genome)
# starts simulator
self.sim.start()
def main():
global P
global CMD_VEL
# Uncomment for debugging if nesssary, recomment before turning in.
# rp.Subscriber('/stage/base_pose_ground_truth', Odometry, mcl_debug.got_odom)
rp.Subscriber('/robot/base_scan', LaserScan, got_scan) # movement/sensor particle update
rp.Subscriber('/robot/cmd_vel', Twist, got_vel)
#actual robot pose only used to show it on map not for partcile filter
rp.Subscriber('/stage/base_pose_ground_truth', Odometry, actual_pose) #actual robot pose
#removed due to wander node
#CMD_VEL = rp.Publisher('/robot/cmd_vel', Twist, queue_size=1)
# create initial particles
for p in xrange(PARTICLE_COUNT):
r = ROBOT()
r.set_pose(5, 5.6, 0) # map space
P.append(r)
mcl_tools.mcl_init('particle_2d')
mcl_tools.mcl_run_viz()
def start_evaluation(self, blind_mode=False):
'''
:param blind_mode: Flag to disable the visualization
Creates an instance of pyrosim and ROBOT
'''
self.sim = pyrosim.Simulator(play_paused=False,
eval_time=1000,
window_size=(1900, 1080),
play_blind=blind_mode)
self.robot = ROBOT(self.sim, self.genome)
self.sim.start()
def __init__(self):
self.sim = PYROSIM(playPaused=False)
self.arena = ARENA(self.sim)
xPosition = random.random()*(c.endX-c.startX) + c.startX
yPosition = random.random()*(c.endY-c.startY) + c.startY
self.robot = ROBOT(self.sim, x = xPosition , y = yPosition , theta = 0.0 )
self.sim.Start()
def Start_Evaluation(self,trialIndex,initialX,initialY,initialTheta,pp,pb):
self.sims[trialIndex] = PYROSIM(playPaused=pp,playBlind=pb)
self.robot = ROBOT(self.sims[trialIndex], self.genome, x = initialX , y = initialY , theta = initialTheta)
del self.robot
self.arena = ARENA(self.sims[trialIndex])
del self.arena
self.sims[trialIndex].Start()
def Start_Evaluation(self, env, pp, pb):
# starts simulation
self.sim = pyrosim.Simulator(play_paused=pp,
eval_time=c.evalTime,
play_blind=pb)
# call to function ROBOT which generates the scissor robot
self.robot = ROBOT(self.sim, self.genome)
env.Send_To(self.sim)
# starts simulator
self.sim.start()
def Start_Evaluation(self, env, pb, pp = False): #---SIMULATOR---# # start the simulator self.sim = pyrosim.Simulator(eval_time = c.evalTime, play_paused = pp, play_blind = pb) #---ROBOTS---# # spawn bot self.robot = ROBOT(self.sim, self.genome) #---ENVIRONMENTS---# env.Send_To(self.sim) #---SIMULATION---# # start the simulation self.sim.start()
def Start_Evaluation(self, pb):
# create a Pyrosim simulator
self.sim = pyrosim.Simulator(play_paused=False,
eval_time=1500,
play_blind=pb,
xyz=[1.0, -2.6, 1.5],
window_size=(415, 280),
hpr=[110, -18, 0])
# create a robot inside the simulator called sim
self.robot = ROBOT(
self.sim, self.genome, self.A, self.B,
self.leg) # create a class instance of the ROBOT class
# start the simulation
self.sim.start()
def Reset(self, database, screen):
numUndigestedReinforcements = database.Get_Num_Undigested_Reinforcements(
)
self.robots = {}
for color in c.colors:
self.robots[color] = ROBOT(database, color, screen,
numUndigestedReinforcements)
self.Compute_Max_Wins_And_Losses()
for color in c.colors:
self.robots[color].Set_Position()
def evaluate(self):
sim = pyrosim.Simulator(play_paused=False,
eval_time=500,
window_size=(1900, 1080))
robot = ROBOT(sim, self.genome)
# Starts simulation
sim.start()
sim.wait_to_finish()
# Position sensor returns [x,y,z] coordinates
# svi 0 -> x
# positionData_x = sim.get_sensor_data(sensor_id=robot.position_red, svi=0)
positionData_y = sim.get_sensor_data(sensor_id=robot.position_red,
svi=1)
# positionData_z = sim.get_sensor_data(sensor_id=robot.position_red, svi=2)
self.fitness = positionData_y[-1]
def Start_Evaluation(self, pb, pp):
#---SIMULATOR---#
# start the simulator
self.sim = pyrosim.Simulator(eval_time=1000,
play_paused=pp,
play_blind=pb)
#---ROBOTS---#
# spawn bot
self.robot = ROBOT(self.sim, self.genome)
#---SIMULATION---#
# start the simulation
self.sim.start()
def Start_Evaluation(self,
env=None,
eval_time=C.evalTime,
play_blind=False):
self.sim = pyrosim.Simulator(eval_time=eval_time,
play_blind=play_blind,
play_paused=True)
self.hasLight = env is not None
self.carry_box = False
if self.hasLight:
env.send_to(self.sim)
self.hasLight = env.hasLight
self.carry_box = env.carry_box
if self.carry_box:
self.p_box = env.p_box
self.robot = ROBOT(self.sim, self.hasLight, self.genome)
self.sim.assign_collision('robot', 'env')
self.sim.assign_collision('env', 'robot')
self.sim.start()