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train_pybullet_racecar.py works, self-driving car drives towards the ball using OpenAI baselines DQN :-)

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See https://www.youtube.com/watch?v=DZ5Px-ocelw for video and how-to-install.
This commit is contained in:
erwincoumans
2017-06-10 18:46:36 -07:00
parent 4a7469a1ba
commit 1752aa55ca
5 changed files with 50 additions and 46 deletions
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25
examples/pybullet/gym/enjoy_pybullet_racecar.py
View File

@@ -6,7 +6,7 @@ from baselines import deepq
def main():
env = RacecarGymEnv(render=True)
env = RacecarGymEnv(renders=True)
act = deepq.load("racecar_model.pkl")
print(act)
while True:
@@ -16,27 +16,8 @@ def main():
print(obs)
episode_rew = 0
while not done:
#env.render()
print("!!!!!!!!!!!!!!!!!!!!!!!!!!")
print("obs")
print(obs)
print("???????????????????????????")
print("obs[None]")
print(obs[None])
o = obs[None]
print("o")
print(o)
aa = act(o)
print("aa")
print (aa)
a = aa[0]
print("a")
print(a)
obs, rew, done, _ = env.step(a)
print("===================================")
print("obs")
print(obs)
env.render()
obs, rew, done, _ = env.step(act(obs[None])[0])
episode_rew += rew
print("Episode reward", episode_rew)

4
examples/pybullet/gym/envs/bullet/racecar.py
View File

@@ -12,7 +12,7 @@ class Racecar:
def reset(self):
self.racecarUniqueId = p.loadURDF("racecar/racecar.urdf", [0,0,.2])
self.maxForce = 10
self.maxForce = 20
self.nMotors = 2
self.motorizedwheels=[2]
self.inactiveWheels = [3,5,7]
@@ -21,7 +21,7 @@ class Racecar:
self.motorizedWheels = [2]
self.steeringLinks=[4,6]
self.speedMultiplier = 10.
self.speedMultiplier = 4.
def getActionDimension(self):

35
examples/pybullet/gym/envs/bullet/racecarGymEnv.py
View File

@@ -16,9 +16,9 @@ class RacecarGymEnv(gym.Env):
def __init__(self,
urdfRoot="",
actionRepeat=1,
actionRepeat=50,
isEnableSelfCollision=True,
render=True):
renders=True):
print("init")
self._timeStep = 0.01
self._urdfRoot = urdfRoot
@@ -27,9 +27,9 @@ class RacecarGymEnv(gym.Env):
self._observation = []
self._ballUniqueId = -1
self._envStepCounter = 0
self._render = render
self._renders = renders
self._p = p
if self._render:
if self._renders:
p.connect(p.GUI)
else:
p.connect(p.DIRECT)
@@ -49,9 +49,14 @@ class RacecarGymEnv(gym.Env):
#p.setPhysicsEngineParameter(numSolverIterations=300)
p.setTimeStep(self._timeStep)
#p.loadURDF("%splane.urdf" % self._urdfRoot)
p.loadSDF("%sstadium.sdf" % self._urdfRoot)
stadiumobjects = p.loadSDF("%sstadium.sdf" % self._urdfRoot)
#move the stadium objects slightly above 0
for i in stadiumobjects:
pos,orn = p.getBasePositionAndOrientation(i)
newpos = [pos[0],pos[1],pos[2]+0.1]
p.resetBasePositionAndOrientation(i,newpos,orn)
dist = 1.+10.*random.random()
dist = 5 +2.*random.random()
ang = 2.*3.1415925438*random.random()
ballx = dist * math.sin(ang)
@@ -75,25 +80,29 @@ class RacecarGymEnv(gym.Env):
return [seed]
def getExtendedObservation(self):
self._observation = self._racecar.getObservation()
pos,orn = p.getBasePositionAndOrientation(self._ballUniqueId)
self._observation.extend(list(pos))
self._observation = [] #self._racecar.getObservation()
carpos,carorn = p.getBasePositionAndOrientation(self._racecar.racecarUniqueId)
ballpos,ballorn = p.getBasePositionAndOrientation(self._ballUniqueId)
invCarPos,invCarOrn = p.invertTransform(carpos,carorn)
ballPosInCar,ballOrnInCar = p.multiplyTransforms(invCarPos,invCarOrn,ballpos,ballorn)
self._observation.extend([ballPosInCar[0],ballPosInCar[1]])
return self._observation
def _step(self, action):
if (self._render):
if (self._renders):
basePos,orn = p.getBasePositionAndOrientation(self._racecar.racecarUniqueId)
#p.resetDebugVisualizerCamera(1, 30, -40, basePos)
fwd = [-1,-1,-1,0,0,0,1,1,1]
steerings = [-0.5,0,0.5,-0.5,0,0.5,-0.5,0,0.5]
fwd = [-5,-5,-5,0,0,0,5,5,5]
steerings = [-0.3,0,0.3,-0.3,0,0.3,-0.3,0,0.3]
forward = fwd[action]
steer = steerings[action]
realaction = [forward,steer]
self._racecar.applyAction(realaction)
for i in range(self._actionRepeat):
p.stepSimulation()
if self._render:
if self._renders:
time.sleep(self._timeStep)
self._observation = self.getExtendedObservation()

20
examples/pybullet/gym/racecarGymEnvTest.py
View File

@@ -9,6 +9,22 @@ steeringSlider = environment._p.addUserDebugParameter("steering",-0.5,0.5,0)
while (True):
targetVelocity = environment._p.readUserDebugParameter(targetVelocitySlider)
steeringAngle = environment._p.readUserDebugParameter(steeringSlider)
action=[targetVelocity,steeringAngle]
discreteAction = 0
if (targetVelocity<-0.33):
discreteAction=0
else:
if (targetVelocity>0.33):
discreteAction=6
else:
discreteAction=3
if (steeringAngle>-0.17):
if (steeringAngle>0.17):
discreteAction=discreteAction+2
else:
discreteAction=discreteAction+1
action=discreteAction
state, reward, done, info = environment.step(action)
obs = environment.getExtendedObservation()
print("obs")
print(obs)

12
examples/pybullet/gym/train_pybullet_racecar.py
View File

@@ -9,23 +9,21 @@ import datetime
def callback(lcl, glb):
# stop training if reward exceeds 199
is_solved = lcl['t'] > 100 and sum(lcl['episode_rewards'][-101:-1]) / 100 >= 199
#uniq_filename = "racecar_model" + str(datetime.datetime.now().date()) + '_' + str(datetime.datetime.now().time()).replace(':', '.')
#print("uniq_filename=")
#print(uniq_filename)
#act.save(uniq_filename)
total = sum(lcl['episode_rewards'][-101:-1]) / 100
totalt = lcl['t']
is_solved = totalt > 2000 and total >= -50
return is_solved
def main():
env = RacecarGymEnv(render=False)
env = RacecarGymEnv(renders=False)
model = deepq.models.mlp([64])
act = deepq.learn(
env,
q_func=model,
lr=1e-3,
max_timesteps=10000000,
max_timesteps=10000,
buffer_size=50000,
exploration_fraction=0.1,
exploration_final_eps=0.02,