diff --git a/alr_envs/mujoco/alr_reacher.py b/alr_envs/mujoco/alr_reacher.py
index cbaec6c..d72c9ce 100644
--- a/alr_envs/mujoco/alr_reacher.py
+++ b/alr_envs/mujoco/alr_reacher.py
@@ -8,13 +8,13 @@ from alr_envs.utils.utils import angle_normalize
 
 
 class ALRReacherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
-    def __init__(self, steps_before_reward=200, n_links=5, balance=False):
+    def __init__(self, steps_before_reward=200, n_links=5, balance=True):
         self._steps = 0
         self.steps_before_reward = steps_before_reward
         self.n_links = n_links
 
         self.balance = balance
-        self.balance_weight = 0.01
+        self.balance_weight = 0.5
 
         self.reward_weight = 1
         if steps_before_reward == 200:
@@ -29,7 +29,7 @@ class ALRReacherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
         else:
             raise ValueError(f"Invalid number of links {n_links}, only 5 or 7 allowed.")
 
-        utils.EzPickle.__init__(self)
+        utils.EzPickle.__init__(**locals())
         mujoco_env.MujocoEnv.__init__(self, os.path.join(os.path.dirname(__file__), "assets", file_name), 2)
 
     def step(self, a):
@@ -45,7 +45,7 @@ class ALRReacherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
         reward_ctrl = - np.square(a).sum()
 
         if self.balance:
-            reward_balance = - self.balance_weight * np.abs(
+            reward_balance -= self.balance_weight * np.abs(
                 angle_normalize(np.sum(self.sim.data.qpos.flat[:self.n_links]), type="rad"))
 
         reward = reward_dist + reward_ctrl + angular_vel + reward_balance
@@ -58,7 +58,7 @@ class ALRReacherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
                                       goal=self.goal if hasattr(self, "goal") else None)
 
     def viewer_setup(self):
-        self.viewer.cam.trackbodyid = 0
+        self.viewer.cam.trackbodyid = 1
 
     def reset_model(self):
         qpos = self.np_random.uniform(low=-0.1, high=0.1, size=self.model.nq) + self.init_qpos