diff --git a/fancy_gym/envs/mujoco/table_tennis/mp_wrapper.py b/fancy_gym/envs/mujoco/table_tennis/mp_wrapper.py
index e33ed6c..3e5a464 100644
--- a/fancy_gym/envs/mujoco/table_tennis/mp_wrapper.py
+++ b/fancy_gym/envs/mujoco/table_tennis/mp_wrapper.py
@@ -7,6 +7,53 @@ from fancy_gym.envs.mujoco.table_tennis.table_tennis_utils import jnt_pos_low, j
 
 
 class TT_MPWrapper(RawInterfaceWrapper):
+    mp_config = {
+        'ProMP': {
+            'phase_generator_kwargs': {
+                'learn_tau': False,
+                'learn_delay': False,
+                'tau_bound': [0.8, 1.5],
+                'delay_bound': [0.05, 0.15],
+            },
+            'controller_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]),
+            },
+            'basis_generator_kwargs': {
+                'num_basis': 3,
+                'num_basis_zero_start': 1,
+                'num_basis_zero_goal': 1,
+            },
+            'black_box_kwargs': {
+                'verbose': 2,
+            },
+        },
+        'DMP': {},
+        'ProDMP': {
+            'phase_generator_kwargs': {
+                'learn_tau': True,
+                'learn_delay': True,
+                'tau_bound': [0.8, 1.5],
+                'delay_bound': [0.05, 0.15],
+                'alpha_phase': 3,
+            },
+            'controller_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]),
+            },
+            'basis_generator_kwargs': {
+                'num_basis': 3,
+                'alpha': 25,
+                'basis_bandwidth_factor': 3,
+            },
+            'trajectory_generator_kwargs': {
+                'weights_scale': 0.7,
+                'auto_scale_basis': True,
+                'relative_goal': True,
+                'disable_goal': True,
+            },
+        },
+    }
 
     # Random x goal + random init pos
     @property
@@ -16,7 +63,7 @@ class TT_MPWrapper(RawInterfaceWrapper):
             [False] * 7,  # joints velocity
             [True] * 2,  # position ball x, y
             [False] * 1,  # position ball z
-            #[True] * 3,    # velocity ball x, y, z
+            # [True] * 3,    # velocity ball x, y, z
             [True] * 2,  # target landing position
             # [True] * 1,  # time
         ])
@@ -39,7 +86,42 @@ class TT_MPWrapper(RawInterfaceWrapper):
                               return_contextual_obs: bool) -> Tuple[np.ndarray, float, bool, dict]:
         return self.get_invalid_traj_step_return(action, pos_traj, return_contextual_obs)
 
+
+class TT_MPWrapper_Replan(TT_MPWrapper):
+    mp_config = {
+        'ProMP': {},
+        'DMP': {},
+        'ProDMP': {
+            'phase_generator_kwargs': {
+                'learn_tau': True,
+                'learn_delay': True,
+                'tau_bound': [0.8, 1.5],
+                'delay_bound': [0.05, 0.15],
+                'alpha_phase': 3,
+            },
+            'controller_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]),
+            },
+            'basis_generator_kwargs': {
+                'num_basis': 2,
+                'alpha': 25,
+                'basis_bandwidth_factor': 3,
+            },
+            'trajectory_generator_kwargs': {
+                'auto_scale_basis': True,
+                'goal_offset': 1.0,
+            },
+            'black_box_kwargs': {
+                'max_planning_times': 3,
+                'replanning_schedule': lambda pos, vel, obs, action, t: t % 50 == 0,
+            },
+        },
+    }
+
+
 class TTVelObs_MPWrapper(TT_MPWrapper):
+    # Will inherit mp_config from TT_MPWrapper
 
     @property
     def context_mask(self):
@@ -51,4 +133,20 @@ class TTVelObs_MPWrapper(TT_MPWrapper):
             [True] * 3,    # velocity ball x, y, z
             [True] * 2,  # target landing position
             # [True] * 1,  # time
-        ])
\ No newline at end of file
+        ])
+
+
+class TTVelObs_MPWrapper_Replan(TT_MPWrapper_Replan):
+    # Will inherit mp_config from TT_MPWrapper_Replan
+
+    @property
+    def context_mask(self):
+        return np.hstack([
+            [False] * 7,  # joints position
+            [False] * 7,  # joints velocity
+            [True] * 2,  # position ball x, y
+            [False] * 1,  # position ball z
+            [True] * 3,    # velocity ball x, y, z
+            [True] * 2,  # target landing position
+            # [True] * 1,  # time
+        ])