diff --git a/alr_envs/classic_control/hole_reacher.py b/alr_envs/classic_control/hole_reacher.py
index 681183b..96c64f7 100644
--- a/alr_envs/classic_control/hole_reacher.py
+++ b/alr_envs/classic_control/hole_reacher.py
@@ -99,7 +99,10 @@ class HoleReacher(gym.Env):
             if self._steps == 199:
                 reward = - np.linalg.norm(self.end_effector - self.bottom_center_of_hole) ** 2
         else:
-            reward = -self.collision_penalty
+            if self.collision_penalty != 0:
+                reward = -self.collision_penalty
+            else:
+                reward = - np.linalg.norm(self.end_effector - self.bottom_center_of_hole) ** 2
 
         reward -= 5e-8 * np.sum(acc ** 2)
 
diff --git a/alr_envs/classic_control/utils.py b/alr_envs/classic_control/utils.py
index b26246f..1aaafb1 100644
--- a/alr_envs/classic_control/utils.py
+++ b/alr_envs/classic_control/utils.py
@@ -134,18 +134,18 @@ def make_holereacher_env_pmp(rank, seed=0):
                            hole_width=0.15,
                            hole_depth=1,
                            hole_x=1,
-                           collision_penalty=1000)
+                           collision_penalty=100)
 
         _env = DetPMPEnvWrapper(_env,
                                 num_dof=5,
                                 num_basis=5,
-                                width=0.005,
+                                width=0.025,
                                 policy_type="velocity",
                                 start_pos=_env.start_pos,
                                 duration=2,
                                 post_traj_time=0,
                                 dt=_env.dt,
-                                weights_scale=0.25,
+                                weights_scale=0.2,
                                 zero_start=True,
                                 zero_goal=False
                                 )
diff --git a/dmp_env_wrapper_example.py b/dmp_env_wrapper_example.py
index ed86423..2e526e5 100644
--- a/dmp_env_wrapper_example.py
+++ b/dmp_env_wrapper_example.py
@@ -1,5 +1,5 @@
 from alr_envs.classic_control.utils import make_viapointreacher_env
-from alr_envs.classic_control.utils import make_holereacher_env, make_holereacher_fix_goal_env
+from alr_envs.classic_control.utils import make_holereacher_env, make_holereacher_fix_goal_env, make_holereacher_env_pmp
 from alr_envs.utils.dmp_async_vec_env import DmpAsyncVectorEnv
 import numpy as np
 
@@ -8,22 +8,21 @@ if __name__ == "__main__":
 
     n_samples = 1
     n_cpus = 4
-    dim = 30
+    dim = 15
 
     # env = DmpAsyncVectorEnv([make_viapointreacher_env(i) for i in range(n_cpus)],
     #                         n_samples=n_samples)
 
-    test_env = make_holereacher_env(0)()
+    test_env = make_holereacher_env_pmp(0)()
 
-    # params = np.random.randn(n_samples, dim)
-    params = np.array([  0.57622273,   0.98294602,   1.48964131,   0.65430972,
-        -0.26028221,   4.84693322,   1.77366128,   0.51080511,
-        -2.38201107,  -0.84990048,   1.02289828,   1.20675551,
-         0.38075566,  -1.84282938,  -3.48690172,   2.17434711,
-        -1.79285349,  -1.7533641 ,   0.62802966,   1.18928357,
-         0.2818753 ,  -3.27708291,  -0.91761804,  -0.38350967,
-         2.25849139,  21.57786524, -14.38494647, -11.5380005 ,
-       -11.09529721,  -0.39453533])
+    # params = 1 * np.random.randn(dim)
+    params = np.array([[ -0.13106822,  -0.66268577,  -1.37025136,  -1.34813613,
+         -0.34040336,  -1.41684643,   2.81882318,  -1.93383471,
+         -5.84213385,  -3.8623558 ,  -1.31946267,   3.19346678,
+         -9.6581148 ,  -8.27402906,  -0.42374776,  -2.06852054,
+          7.21224904,  -6.81061422,  -9.54973119,  -6.18636867,
+         -6.82998929,  13.00398992, -18.28106949,  -6.06678165,
+          2.79744735]])
 
     # params = np.hstack([50 * np.random.randn(n_samples, 25), np.tile(np.array([np.pi/2, -np.pi/4, -np.pi/4, -np.pi/4, -np.pi/4]), [n_samples, 1])])