docs(thruster): add missing __init__ arg descriptions

Author: grzemal

source/isaaclab/isaaclab/actuators/thruster.py

@@ -57,9 +57,13 @@ def __init__(
         """Construct buffers and sample per-motor parameters.
 
         Args:
-            num_envs: Number of vectorized envs.
             cfg: Thruster configuration.
-            device: PyTorch device string.
+            thruster_names: List of thruster names belonging to this group.
+            thruster_ids: Slice or tensor of indices into the articulation thruster array.
+            num_envs: Number of parallel/vectorized environments.
+            device: PyTorch device string or device identifier.
+            init_thruster_rps: Initial per-thruster rotations-per-second tensor used when
+                the configuration uses RPM-based thrust modelling.
         """
         self.cfg = cfg
         self._num_envs = num_envs
@@ -166,7 +170,6 @@ def compute(self, control_action: ArticulationThrustActions) -> ArticulationThru
 
         control_action.thrusts = self.applied_thrust
 
-
         return control_action
 
     def reset_idx(self, env_ids=None) -> None:

source/isaaclab_tasks/isaaclab_tasks/manager_based/drone_ntnu/mdp/rewards.py

@@ -39,6 +39,7 @@ def distance_to_goal_exp(
     position_error_square = torch.sum(torch.square(target_position_w - current_position), dim=1)
     return torch.exp(-position_error_square / std**2)
 
+
 def upright_posture_reward(
     env: ManagerBasedRLEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg("robot"), std: float = 0.5
 ) -> torch.Tensor:
@@ -72,6 +73,7 @@ def ang_vel_reward(
     angular_vel_reward = torch.exp(-ang_vel_squared / std**2)
     return angular_vel_reward
 
+
 def velocity_reward(
     env: ManagerBasedRLEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg("robot"), std: float = 1.0
 ) -> torch.Tensor:

source/isaaclab_tasks/isaaclab_tasks/manager_based/drone_ntnu/state_based_control/config/LMF2/state_based_control_env_cfg.py

@@ -176,9 +176,9 @@ class RewardsCfg:
     upright_posture = RewTerm(
         func=mdp.upright_posture_reward, weight=1.0, params={"asset_cfg": SceneEntityCfg("robot"), "std": 5.0}  # 0.5
     )
-    
+
     yaw_aligned = RewTerm(func=mdp.yaw_reward, weight=2.0, params={"asset_cfg": SceneEntityCfg("robot"), "std": 1.0})
-    
+
     velocity_reward = RewTerm(
         func=mdp.velocity_reward,
         weight=2.5,