Revised reward, terminated, truncated in RL aviaries

utiasDSL · Nov 19, 2023 · 1b14a1a · 1b14a1a
1 parent 85a726d
commit 1b14a1a
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Showing 2 changed files with 6 additions and 6 deletions.
diff --git a/gym_pybullet_drones/envs/HoverAviary.py b/gym_pybullet_drones/envs/HoverAviary.py
@@ -48,7 +48,7 @@ def __init__(self,
             The type of action space (1 or 3D; RPMS, thurst and torques, or waypoint with PID control)
 
         """
-        self.target_pos = np.array([0,0,1])
+        self.TARGET_POS = np.array([0,0,1])
         super().__init__(drone_model=drone_model,
                          num_drones=1,
                          initial_xyzs=initial_xyzs,
@@ -74,7 +74,7 @@ def _computeReward(self):
 
         """
         state = self._getDroneStateVector(0)
-        ret = max(0, 500 - np.linalg.norm(self.target_pos-state[0:3])**2)
+        ret = max(0, 500 - np.linalg.norm(self.TARGET_POS-state[0:3])**2)
         return ret
 
     ################################################################################
@@ -89,7 +89,7 @@ def _computeTerminated(self):
 
         """
         state = self._getDroneStateVector(0)
-        if np.linalg.norm(self.target_pos-state[0:3]) < .001:
+        if np.linalg.norm(self.TARGET_POS-state[0:3]) < .001:
             return True
         else:
             return False

diff --git a/gym_pybullet_drones/envs/LeaderFollowerAviary.py b/gym_pybullet_drones/envs/LeaderFollowerAviary.py
@@ -54,7 +54,7 @@ def __init__(self,
             The type of action space (1 or 3D; RPMS, thurst and torques, or waypoint with PID control)
 
         """
-        self.target_pos = np.array([0,0,1])
+        self.TARGET_POS = np.array([0,0,1])
         super().__init__(drone_model=drone_model,
                          num_drones=num_drones,
                          neighbourhood_radius=neighbourhood_radius,
@@ -82,7 +82,7 @@ def _computeReward(self):
         """
         rewards = np.zeros(self.NUM_DRONES)
         states = np.array([self._getDroneStateVector(i) for i in range(self.NUM_DRONES)])
-        ret = max(0, 500 - np.linalg.norm(self.target_pos-states[0, 0:3])**2)
+        ret = max(0, 500 - np.linalg.norm(self.TARGET_POS-states[0, 0:3])**2)
         for i in range(1, self.NUM_DRONES):
             ret += max(0, 100 - np.linalg.norm(states[i-1, 3]-states[i, 3])**2)
         return ret
@@ -99,7 +99,7 @@ def _computeTerminated(self):
 
         """
         state = self._getDroneStateVector(0)
-        if np.linalg.norm(self.target_pos-state[0:3]) < .001:
+        if np.linalg.norm(self.TARGET_POS-state[0:3]) < .001:
             return True
         else:
             return False