diff --git a/alr_envs/alr/__init__.py b/alr_envs/alr/__init__.py
index 026f1a7..917e102 100644
--- a/alr_envs/alr/__init__.py
+++ b/alr_envs/alr/__init__.py
@@ -236,16 +236,6 @@ register(
         }
     )
 
-# Beerpong devel big table
-register(
-        id='ALRBeerPong-v3',
-        entry_point='alr_envs.alr.mujoco:ALRBeerBongEnv',
-        max_episode_steps=600,
-        kwargs={
-            "rndm_goal": True,
-            "cup_goal_pos": [-0.3, -1.2]
-        }
-    )
 
 # Motion Primitive Environments
 
@@ -413,32 +403,6 @@ for _v in _versions:
     )
     ALL_ALR_MOTION_PRIMITIVE_ENVIRONMENTS["ProMP"].append(_env_id)
 
-## Beerpong- Big table devel
-
-register(
-        id='BeerpongProMP-v3',
-        entry_point='alr_envs.utils.make_env_helpers:make_promp_env_helper',
-        kwargs={
-            "name": f"alr_envs:ALRBeerPong-v3",
-            "wrappers": [mujoco.beerpong.MPWrapper],
-            "mp_kwargs": {
-                "num_dof": 7,
-                "num_basis": 5,
-                "duration": 1,
-                "post_traj_time": 2,
-                "policy_type": "motor",
-                "weights_scale": 1,
-                "zero_start": True,
-                "zero_goal": False,
-                "policy_kwargs": {
-                    "p_gains": np.array([       1.5,   5,   2.55,    3,   2.,    2,   1.25]),
-                    "d_gains": np.array([0.02333333, 0.1, 0.0625, 0.08, 0.03, 0.03, 0.0125])
-                }
-            }
-        }
-    )
-ALL_ALR_MOTION_PRIMITIVE_ENVIRONMENTS["ProMP"].append('BeerpongProMP-v3')
-
 ## Table Tennis
 ctxt_dim = [2, 4]
 for _v, cd in enumerate(ctxt_dim):
@@ -453,7 +417,7 @@ for _v, cd in enumerate(ctxt_dim):
                 "num_dof": 7,
                 "num_basis": 2,
                 "duration": 1.25,
-                "post_traj_time": 1.5,
+                "post_traj_time": 4.5,
                 "policy_type": "motor",
                 "weights_scale": 1.0,
                 "zero_start": True,
@@ -467,28 +431,28 @@ for _v, cd in enumerate(ctxt_dim):
     )
     ALL_ALR_MOTION_PRIMITIVE_ENVIRONMENTS["ProMP"].append(_env_id)
 
-register(
-    id='TableTennisProMP-v2',
-    entry_point='alr_envs.utils.make_env_helpers:make_promp_env_helper',
-    kwargs={
-        "name": "alr_envs:TableTennis2DCtxt-v1",
-        "wrappers": [mujoco.table_tennis.MPWrapper],
-        "mp_kwargs": {
-            "num_dof": 7,
-            "num_basis": 2,
-            "duration": 1.,
-            "post_traj_time": 2.5,
-            "policy_type": "motor",
-            "weights_scale": 1,
-            "off": -0.05,
-            "bandwidth_factor": 3.5,
-            "zero_start": True,
-            "zero_goal": False,
-            "policy_kwargs": {
-                "p_gains": 0.5*np.array([1.0, 4.0, 2.0, 4.0, 1.0, 4.0, 1.0]),
-                "d_gains": 0.5*np.array([0.1, 0.4, 0.2, 0.4, 0.1, 0.4, 0.1])
-            }
-        }
-    }
-)
-ALL_ALR_MOTION_PRIMITIVE_ENVIRONMENTS["ProMP"].append("TableTennisProMP-v2")
+# register(
+#     id='TableTennisProMP-v2',
+#     entry_point='alr_envs.utils.make_env_helpers:make_promp_env_helper',
+#     kwargs={
+#         "name": "alr_envs:TableTennis2DCtxt-v1",
+#         "wrappers": [mujoco.table_tennis.MPWrapper],
+#         "mp_kwargs": {
+#             "num_dof": 7,
+#             "num_basis": 2,
+#             "duration": 1.25,
+#             "post_traj_time": 4.5,
+#             #"width": 0.01,
+#             #"off": 0.01,
+#             "policy_type": "motor",
+#             "weights_scale": 1.0,
+#             "zero_start": True,
+#             "zero_goal": False,
+#             "policy_kwargs": {
+#                 "p_gains": 0.5*np.array([1.0, 4.0, 2.0, 4.0, 1.0, 4.0, 1.0]),
+#                 "d_gains": 0.5*np.array([0.1, 0.4, 0.2, 0.4, 0.1, 0.4, 0.1])
+#             }
+#         }
+#     }
+# )
+# ALL_ALR_MOTION_PRIMITIVE_ENVIRONMENTS["ProMP"].append("TableTennisProMP-v2")
diff --git a/alr_envs/alr/mujoco/table_tennis/tt_gym.py b/alr_envs/alr/mujoco/table_tennis/tt_gym.py
index e88bbc5..c93cd26 100644
--- a/alr_envs/alr/mujoco/table_tennis/tt_gym.py
+++ b/alr_envs/alr/mujoco/table_tennis/tt_gym.py
@@ -11,7 +11,8 @@ from alr_envs.alr.mujoco.table_tennis.tt_reward import TT_Reward
 #TODO: Check for simulation stability. Make sure the code runs even for sim crash
 
 # MAX_EPISODE_STEPS = 1750
-MAX_EPISODE_STEPS = 1375
+# MAX_EPISODE_STEPS = 1375
+MAX_EPISODE_STEPS = 2875
 BALL_NAME_CONTACT = "target_ball_contact"
 BALL_NAME = "target_ball"
 TABLE_NAME = 'table_tennis_table'