diff --git a/fancy_gym/black_box/black_box_wrapper.py b/fancy_gym/black_box/black_box_wrapper.py
index 735efec..3b3ac55 100644
--- a/fancy_gym/black_box/black_box_wrapper.py
+++ b/fancy_gym/black_box/black_box_wrapper.py
@@ -70,7 +70,10 @@ class BlackBoxWrapper(gym.ObservationWrapper):
         # tricky_action_upperbound = [np.inf] * (self.traj_gen_action_space.shape[0] - 7)
         # tricky_action_lowerbound = [-np.inf] * (self.traj_gen_action_space.shape[0] - 7)
         # self.action_space = spaces.Box(np.array(tricky_action_lowerbound), np.array(tricky_action_upperbound), dtype=np.float32)
-
+        self.action_space.low[0] = 0.5
+        self.action_space.high[0] = 1.5
+        self.action_space.low[1] = 0.05
+        self.action_space.high[1] = 0.2
         self.observation_space = self._get_observation_space()
 
         # rendering
diff --git a/fancy_gym/envs/mujoco/table_tennis/table_tennis_env.py b/fancy_gym/envs/mujoco/table_tennis/table_tennis_env.py
index f169e6a..93f1c29 100644
--- a/fancy_gym/envs/mujoco/table_tennis/table_tennis_env.py
+++ b/fancy_gym/envs/mujoco/table_tennis/table_tennis_env.py
@@ -10,9 +10,9 @@ import mujoco
 
 MAX_EPISODE_STEPS_TABLE_TENNIS = 250
 
-CONTEXT_BOUNDS_2DIMS = np.array([[-1.2, -0.6], [-0.2, 0.0]])
-CONTEXT_BOUNDS_4DIMS = np.array([[-1.2, -0.6, -1.0, -0.65],
-                                 [-0.2, 0.6, -0.2, 0.65]])
+CONTEXT_BOUNDS_2DIMS = np.array([[-1.0, -0.65], [-0.2, 0.65]])
+CONTEXT_BOUNDS_4DIMS = np.array([[-1.0, -0.65, -1.0, -0.65],
+                                 [-0.2, 0.65, -0.2, 0.65]])
 
 
 class TableTennisEnv(MujocoEnv, utils.EzPickle):
diff --git a/fancy_gym/examples/examples_movement_primitives.py b/fancy_gym/examples/examples_movement_primitives.py
index f095d4a..a99d6b0 100644
--- a/fancy_gym/examples/examples_movement_primitives.py
+++ b/fancy_gym/examples/examples_movement_primitives.py
@@ -22,7 +22,6 @@ def example_mp(env_name="HoleReacherProMP-v0", seed=1, iterations=1, render=True
     returns = 0
     # env.render(mode=None)
     obs = env.reset()
-    print(obs)
 
     # number of samples/full trajectories (multiple environment steps)
     for i in range(iterations):
@@ -51,7 +50,7 @@ def example_mp(env_name="HoleReacherProMP-v0", seed=1, iterations=1, render=True
         if done:
             # print(reward)
             obs = env.reset()
-            print(obs)
+            print("steps: {}".format(info["num_steps"][-1]))
 
 
 def example_custom_mp(env_name="Reacher5dProMP-v0", seed=1, iterations=1, render=True):
@@ -166,7 +165,7 @@ if __name__ == '__main__':
     # ProMP
     # example_mp("HoleReacherProMP-v0", seed=10, iterations=5, render=render)
     # example_mp("BoxPushingTemporalSparseProMP-v0", seed=10, iterations=1, render=render)
-    example_mp("TableTennis4DProMP-v0", seed=10, iterations=5, render=render)
+    example_mp("TableTennis4DProMP-v0", seed=10, iterations=10, render=True)
 
     # ProDMP
     # example_mp("BoxPushingDenseProDMP-v0", seed=10, iterations=16, render=render)