diff --git a/alr_envs/__init__.py b/alr_envs/__init__.py
index 24353b2..a308852 100644
--- a/alr_envs/__init__.py
+++ b/alr_envs/__init__.py
@@ -178,7 +178,7 @@ register(
         "hole_width": None,
         "hole_depth": 1,
         "hole_x": None,
-        "collision_penalty": 100,
+        "collision_penalty": 1000,
     }
 )
 
@@ -210,7 +210,7 @@ register(
         "hole_width": 0.25,
         "hole_depth": 1,
         "hole_x": 2,
-        "collision_penalty": 2,
+        "collision_penalty": 1000,
     }
 )
 
diff --git a/alr_envs/mujoco/ball_in_a_cup/ball_in_a_cup.py b/alr_envs/mujoco/ball_in_a_cup/ball_in_a_cup.py
index bfd7940..fdd299e 100644
--- a/alr_envs/mujoco/ball_in_a_cup/ball_in_a_cup.py
+++ b/alr_envs/mujoco/ball_in_a_cup/ball_in_a_cup.py
@@ -43,7 +43,7 @@ class ALRBallInACupEnv(alr_mujoco_env.AlrMujocoEnv, utils.EzPickle):
             from alr_envs.mujoco.ball_in_a_cup.ball_in_a_cup_reward import BallInACupReward
             reward_function = BallInACupReward
         else:
-            raise ValueError("Unknown reward type")
+            raise ValueError("Unknown reward type: {}".format(reward_type))
         self.reward_function = reward_function(self.sim_steps)
 
     @property
@@ -106,7 +106,7 @@ class ALRBallInACupEnv(alr_mujoco_env.AlrMujocoEnv, utils.EzPickle):
             done = success or self._steps == self.sim_steps - 1 or is_collided
             self._steps += 1
         else:
-            reward = -2
+            reward = -2000
             success = False
             is_collided = False
             done = True
@@ -154,6 +154,22 @@ class ALRBallInACupEnv(alr_mujoco_env.AlrMujocoEnv, utils.EzPickle):
         des_vel_full[5] = des_vel[2]
         return des_vel_full
 
+    def render(self, render_mode, **render_kwargs):
+        if render_mode == "plot_trajectory":
+            if self._steps == 1:
+                import matplotlib.pyplot as plt
+                # plt.ion()
+                self.fig, self.axs = plt.subplots(3, 1)
+
+            if self._steps <= 1750:
+                for ax, cp in zip(self.axs, self.current_pos[1::2]):
+                    ax.scatter(self._steps, cp, s=2, marker=".")
+
+            # self.fig.show()
+
+        else:
+            super().render(render_mode, **render_kwargs)
+
 
 if __name__ == "__main__":
     env = ALRBallInACupEnv()
diff --git a/alr_envs/mujoco/ball_in_a_cup/ball_in_a_cup_reward_simple.py b/alr_envs/mujoco/ball_in_a_cup/ball_in_a_cup_reward_simple.py
index 0bc0fd2..8f0c588 100644
--- a/alr_envs/mujoco/ball_in_a_cup/ball_in_a_cup_reward_simple.py
+++ b/alr_envs/mujoco/ball_in_a_cup/ball_in_a_cup_reward_simple.py
@@ -22,7 +22,7 @@ class BallInACupReward(alr_reward_fct.AlrReward):
         self.goal_final_id = None
         self.collision_ids = None
         self._is_collided = False
-        self.collision_penalty = 1
+        self.collision_penalty = 1000
 
         self.ball_traj = None
         self.dists = None
@@ -74,11 +74,11 @@ class BallInACupReward(alr_reward_fct.AlrReward):
             # cost_angle = (angle_min_dist - np.pi / 2)**2
 
 
-            min_dist = self.dists[t_min_dist]
+            # min_dist = self.dists[t_min_dist]
             dist_final = self.dists_final[-1]
             min_dist_final = np.min(self.dists_final)
 
-            cost = 0.5 * dist_final + 0.05 * cost_angle  # TODO: Increase cost_angle weight  # 0.5 * min_dist +
+            # cost = 0.5 * dist_final + 0.05 * cost_angle  # TODO: Increase cost_angle weight  # 0.5 * min_dist +
             # reward = np.exp(-2 * cost) - 1e-2 * action_cost - self.collision_penalty * int(self._is_collided)
             # reward = - dist_final**2 - 1e-4 * cost_angle - 1e-5 * action_cost - self.collision_penalty * int(self._is_collided)
             reward = - dist_final**2 - min_dist_final**2 - 1e-4 * cost_angle - 5e-4 * action_cost - self.collision_penalty * int(self._is_collided)
diff --git a/example.py b/example.py
index a8ae649..20fd165 100644
--- a/example.py
+++ b/example.py
@@ -106,10 +106,10 @@ def example_async_contextual_sampler(env_name="alr_envs:SimpleReacherDMP-v1", n_
 
 if __name__ == '__main__':
     # example_mujoco()
-    example_mp("alr_envs:SimpleReacherDMP-v1")
+    # example_mp("alr_envs:SimpleReacherDMP-v1")
     # example_async("alr_envs:LongSimpleReacherDMP-v0", 4)
     # example_async_contextual_sampler()
     # env = gym.make("alr_envs:HoleReacherDetPMP-v1")
-    # env_name = "alr_envs:ALRBallInACupSimpleDetPMP-v0"
-    # example_async_sampler(env_name)
+    env_name = "alr_envs:ALRBallInACupSimpleDetPMP-v0"
+    example_async_sampler(env_name)
     # example_mp(env_name)