diff --git a/mani_skill2/envs/pick_and_place/pick_single.py b/mani_skill2/envs/pick_and_place/pick_single.py
index 17ac063e6..42872127e 100644
--- a/mani_skill2/envs/pick_and_place/pick_single.py
+++ b/mani_skill2/envs/pick_and_place/pick_single.py
@@ -218,6 +218,45 @@ def evaluate(self, **kwargs):
         )
 
     def compute_dense_reward(self, info, **kwargs):
+
+        # Sep. 14, 2022:
+        # We changed the original complex reward to simple reward,
+        # since the original reward can be unfriendly for RL,
+        # even though MPC can solve many objects through the original reward.
+
+        reward = 0.0
+
+        if info["success"]:
+            reward = 10.0
+        else:
+            obj_pose = self.obj_pose
+
+            # reaching reward
+            tcp_wrt_obj_pose = obj_pose.inv() * self.tcp.pose
+            tcp_to_obj_dist = np.linalg.norm(tcp_wrt_obj_pose.p)
+            reaching_reward = 1 - np.tanh(
+                3.0 * np.maximum(tcp_to_obj_dist - np.linalg.norm(self.model_bbox_size), 0.0)
+            )
+            reward = reward + reaching_reward
+
+            # grasp reward
+            is_grasped = self.agent.check_grasp(self.obj, max_angle=30)
+            reward += 3.0 if is_grasped else 0.0
+
+            # reaching-goal reward
+            if is_grasped:
+                obj_to_goal_pos = self.goal_pos - obj_pose.p
+                obj_to_goal_dist = np.linalg.norm(obj_to_goal_pos)
+                reaching_goal_reward = 3 * (1 - np.tanh(3.0 * obj_to_goal_dist))
+                reward += reaching_goal_reward
+
+        return reward
+    
+    def compute_dense_reward_legacy(self, info, **kwargs):
+        # original complex reward that is geometry-independent,
+        # which ensures that MPC can successfully pick up most objects,
+        # but can be unfriendly for RL.
+        
         reward = 0.0
         # hard code gripper info
         finger_length = 0.025
@@ -324,7 +363,7 @@ def compute_dense_reward(self, info, **kwargs):
                     gripper_width / 2 - self.agent.robot.get_qpos()[-2:]
                 )  # ensures that gripper is open
 
-        return reward
+        return reward    
 
     def render(self, mode="human"):
         if mode in ["human", "rgb_array"]: