Merge pull request #1271 from erwincoumans/master

pybullet: remove 'data' from MANIFEST.in

MANIFEST.in

@@ -5,7 +5,6 @@ recursive-include Extras *.h
 recursive-include Extras *.hpp
 recursive-include src *.h
 recursive-include src *.hpp
-recursive-include data *.*
 recursive-include examples/pybullet/gym *.*
 include examples/ThirdPartyLibs/enet/unix.c
 include examples/OpenGLWindow/X11OpenGLWindow.cpp

examples/pybullet/gym/pybullet_envs/__init__.py

@@ -18,7 +18,7 @@ register(
 
 register(
     id='RacecarBulletEnv-v0',
-    entry_point='pybullet_envs.bullet:RacecarBulletEnv',
+    entry_point='pybullet_envs.bullet:RacecarGymEnv',
     timestep_limit=1000,
     reward_threshold=5.0,
 )

examples/pybullet/gym/pybullet_envs/bullet/minitaur_gym_env.py

@@ -48,13 +48,13 @@ class MinitaurBulletEnv(gym.Env):
                observation_noise_stdev=0.0,
                self_collision_enabled=True,
                motor_velocity_limit=np.inf,
-               pd_control_enabled=False,
+               pd_control_enabled=False,#not needed to be true if accurate motor model is enabled (has its own better PD)
                leg_model_enabled=True,
-               accurate_motor_model_enabled=False,
+               accurate_motor_model_enabled=True,
                motor_kp=1.0,
                motor_kd=0.02,
                torque_control_enabled=False,
-               motor_overheat_protection=False,
+               motor_overheat_protection=True,
                hard_reset=True,
                on_rack=False,
                render=False,

examples/pybullet/gym/pybullet_envs/bullet/racecarGymEnv.py

@@ -43,7 +43,8 @@ class RacecarGymEnv(gym.Env):
     observationDim = 2 #len(self.getExtendedObservation())
     #print("observationDim")
     #print(observationDim) 
-    observation_high = np.array([np.finfo(np.float32).max] * observationDim)    
+    # observation_high = np.array([np.finfo(np.float32).max] * observationDim)    
+    observation_high = np.ones(observationDim) * 1000 #np.inf
     if (isDiscrete):
       self.action_space = spaces.Discrete(9)
     else:
@@ -130,7 +131,19 @@ class RacecarGymEnv(gym.Env):
     return np.array(self._observation), reward, done, {}
 
   def _render(self, mode='human', close=False):
-      return
+      width=320
+      height=200
+      img_arr = self._p.getCameraImage(width,height)
+      w=img_arr[0]
+      h=img_arr[1]
+      rgb=img_arr[2]
+      dep=img_arr[3]
+      #print 'width = %d height = %d' % (w,h)
+      # reshape creates np array
+      np_img_arr = np.reshape(rgb, (h, w, 4))
+      # remove alpha channel
+      np_img_arr = np_img_arr[:, :, :3]
+      return np_img_arr
 
   def _termination(self):
     return self._envStepCounter>1000

examples/pybullet/gym/pybullet_envs/examples/enjoy_pybullet_racecar.py

@@ -12,7 +12,7 @@ from baselines import deepq
 
 def main():
     
-    env = RacecarGymEnv(renders=False,isDiscrete=True)
+    env = RacecarGymEnv(renders=True,isDiscrete=True)
     act = deepq.load("racecar_model.pkl")
     print(act)
     while True:

examples/pybullet/gym/pybullet_envs/examples/racecarGymEnvTest.py

@@ -5,7 +5,7 @@ parentdir = os.path.dirname(os.path.dirname(currentdir))
 os.sys.path.insert(0,parentdir)
 
 from pybullet_envs.bullet.racecarGymEnv import RacecarGymEnv
-isDiscrete = True
+isDiscrete = False
 
 environment = RacecarGymEnv(renders=True, isDiscrete=isDiscrete)
 environment.reset()