Added reward function section

content/posts/go2-tasks/index.md

@@ -17,3 +17,28 @@ The Unitree Go2 Dog is an incredibly advanced robot with an impressive locomotio
 
 
 *This post is still under construction, check out our [Final Presentation](https://docs.google.com/presentation/d/1t-WxQv7l9nbno7PVQyR4ZqkIlAv57PJc0tnwp6PpszA/edit?usp=sharing) for more details*
+
+## Reward Function Design
+The reward function design was where the majority of the work was done to train the robot on different tasks. The Genesis platform offers an end-to-end example of a training script, environment, and evaluation script for teaching the robot to walk. The reward function for walking encouraged the dog to maintain a forward velocity while penalizing deviations from the body height target and from the initial joint points.
+
+```python
+    reward_cfg = {
+        "tracking_sigma": 0.25, # Tolerance for tracking commanded velocity
+        "base_height_target": 0.3, # Target height of main body [m]
+        "feet_height_target": 0.075,  # Desired foot clearance [m]
+        "reward_scales": {
+            "tracking_lin_vel": 1.0, # Reward for matching commanded lin_vel
+            "tracking_ang_vel": 0.2, # Reward for matching commanded ang_vel
+            "lin_vel_z": -1.0,  # Penalty for vertical linear velocity
+            "base_height": -50.0, # Penalty for deviation from target body height
+            "action_rate": -0.005, # Penalty for rapid joint motions
+            "similar_to_default": -0.1,  # Penalty for deviation from default joint angles
+        },
+    }
+    command_cfg = {
+        "num_commands": 3,
+        "lin_vel_x_range": [0.5, 0.5],
+        "lin_vel_y_range": [0, 0],
+        "ang_vel_range": [0, 0],
+    }
+```