fix a number of issues in a series of new Minitaur environments

add them to pybullet_envs through __init__.py
    id='MinitaurReactiveEnv-v0',
    id='MinitaurTrottingEnv-v0',
    id='MinitaurBallGymEnv-v0',
    id='MinitaurStandGymEnv-v0',
    id='MinitaurAlternatingLegsEnv-v0',
    id='MinitaurFourLegStandEnv-v0',

disable reflection of minitaur_four_leg_stand_env, since the floor changes orientation (reflection is a fixed plane with [0,0,1] normal)

from pybullet_envs.minitaur.envs.minitaur_alternating_legs_env import MinitaurAlternatingLegsEnv
from pybullet_envs.minitaur.envs.minitaur_ball_gym_env import MinitaurBallGymEnv
from pybullet_envs.minitaur.envs.minitaur_randomize_terrain_gym_env import MinitaurRandomizeTerrainGymEnv
from pybullet_envs.minitaur.envs.minitaur_reactive_env import MinitaurReactiveEnv
from pybullet_envs.minitaur.envs.minitaur_stand_gym_env import MinitaurStandGymEnv
from pybullet_envs.minitaur.envs.minitaur_trotting_env import MinitaurTrottingEnv
from pybullet_envs.minitaur.envs.minitaur_four_leg_stand_env import MinitaurFourLegStandEnv

examples/pybullet/gym/pybullet_envs/__init__.py

@@ -30,6 +30,53 @@ register(
 )
 
 
+register(
+    id='MinitaurReactiveEnv-v0',
+    entry_point='pybullet_envs.minitaur.envs:MinitaurReactiveEnv',
+    render=True,
+    timestep_limit=1000,
+    reward_threshold=5.0,
+)
+
+
+register(
+    id='MinitaurBallGymEnv-v0',
+    entry_point='pybullet_envs.minitaur.envs:MinitaurBallGymEnv',
+    timestep_limit=1000,
+    reward_threshold=5.0,
+)
+
+
+register(
+    id='MinitaurTrottingEnv-v0',
+    entry_point='pybullet_envs.minitaur.envs:MinitaurTrottingEnv',
+    timestep_limit=1000,
+    reward_threshold=5.0,
+)
+
+register(
+    id='MinitaurStandGymEnv-v0',
+    entry_point='pybullet_envs.minitaur.envs:MinitaurStandGymEnv',
+    timestep_limit=1000,
+    reward_threshold=5.0,
+)
+
+register(
+    id='MinitaurAlternatingLegsEnv-v0',
+    entry_point='pybullet_envs.minitaur.envs:MinitaurAlternatingLegsEnv',
+    timestep_limit=1000,
+    reward_threshold=5.0,
+)
+
+register(
+    id='MinitaurFourLegStandEnv-v0',
+    entry_point='pybullet_envs.minitaur.envs:MinitaurFourLegStandEnv',
+    timestep_limit=1000,
+    reward_threshold=5.0,
+)
+
+
+
 register(
     id='RacecarBulletEnv-v0',
     entry_point='pybullet_envs.bullet:RacecarGymEnv',