Make PyTorch an optional dependency for the batched simulator

pyproject.toml

@@ -29,14 +29,16 @@ dependencies = [
     'pandas',
     'tqdm',
     'gymnasium',
-    'roma',           # For batched sim
-    'torch>=1.11.0',  # For batched sim
-    'torchdiffeq',    # For batched sim
-    'opt-einsum',     # For batched sim
     'timed_count',    # Only for ardupilot sitl example
 ]
 
 [project.optional-dependencies]
+batched = [
+    'torch>=1.11.0',
+    'torchdiffeq',
+    'roma',
+    'opt-einsum',
+]
 learning = [
     'stable_baselines3',
     'tensorboard',
@@ -58,6 +60,10 @@ px4 = [
     'pymavlink',
 ]
 all = [
+    "torch>=1.11.0",
+    "torchdiffeq",
+    "roma",
+    "opt-einsum",
     "stable_baselines3",
     "tensorboard",
     "pytest",

rotorpy/controllers/quadrotor_control.py

@@ -1,6 +1,9 @@
 import numpy as np
-import torch
-import roma
+try:
+    import torch
+    import roma
+except ImportError:
+    pass
 from scipy.spatial.transform import Rotation
 
 class SE3Control(object):

rotorpy/sensors/imu.py

@@ -1,6 +1,9 @@
 import numpy as np
 from scipy.spatial.transform import Rotation
-import torch
+try:
+    import torch
+except ImportError:
+    pass
 import copy
 
 class Imu:

rotorpy/simulate.py

@@ -2,8 +2,11 @@
 from enum import Enum
 import copy
 import numpy as np
-import roma
-import torch
+try:
+    import roma
+    import torch
+except ImportError:
+    pass
 from numpy.linalg import norm
 from scipy.spatial.transform import Rotation
 from time import perf_counter

rotorpy/trajectories/circular_traj.py

@@ -1,5 +1,8 @@
 import numpy as np
-import torch
+try:
+    import torch
+except ImportError:
+    pass
 import sys
 
 class ThreeDCircularTraj(object):

rotorpy/trajectories/hover_traj.py

@@ -1,5 +1,8 @@
 import numpy as np
-import torch
+try:
+    import torch
+except ImportError:
+    pass
 
 class HoverTraj(object):
     """

rotorpy/trajectories/lissajous_traj.py

@@ -1,5 +1,8 @@
 import numpy as np
-import torch
+try:
+    import torch
+except ImportError:
+    pass
 
 """
 Lissajous curves are defined by trigonometric functions parameterized in time. 

rotorpy/trajectories/minsnap.py

@@ -5,7 +5,10 @@
 import cvxopt
 from scipy.linalg import block_diag
 from typing import List
-import torch
+try:
+    import torch
+except ImportError:
+    pass
 
 def cvxopt_solve_qp(P, q, G=None, h=None, A=None, b=None):
     """

rotorpy/trajectories/traj_template.py

@@ -2,7 +2,10 @@
 Imports
 """
 import numpy as np
-import torch
+try:
+    import torch
+except ImportError:
+    pass
 
 class TrajTemplate(object):
     """

rotorpy/vehicles/multirotor.py

@@ -8,9 +8,12 @@
 from scipy.spatial.transform import Rotation as R
 
 # imports for Batched Dynamics
-import torch
-from torchdiffeq import odeint
-import roma
+try:
+    import torch
+    from torchdiffeq import odeint
+    import roma
+except ImportError:
+    pass
 
 import time
 

rotorpy/vehicles/px4_multirotor.py

@@ -285,8 +285,8 @@ def _send_hil_sensor(self, state, statedot):
             fields_updated=updated_bitmask,
         )
 
-    def step(self, state, control, t_step):        
-        
+    def step(self, state, control, t_step):
+
         # Compute state derivative once for state and messages
         # and send both HIL messages
         statedot = self.statedot(state, control, 0.0)
@@ -298,14 +298,13 @@ def step(self, state, control, t_step):
             px4_control = self._fetch_latest_px4_control(blocking=self._lockstep_enabled)
             if px4_control is not None:
                 self._last_control = px4_control
-                control = px4_control
             else:
-                control = self._last_control
+                pass # Do not modify _last_control
 
         else: # In this case we use the control provided by the external controller
-            pass
-        
-        state = super().step(state, control, t_step)
+            self._last_control = control
+
+        state = super().step(state, self._last_control, t_step)
         self.state = state
         self.t += t_step
 

rotorpy/wind/default_winds.py

@@ -1,6 +1,9 @@
 import numpy as np
 import sys
-import torch
+try:
+    import torch
+except ImportError:
+    pass
 import math
 import random
 

rotorpy/wind/dryden_winds.py

@@ -1,5 +1,8 @@
 import numpy as np
-import torch
+try:
+    import torch
+except ImportError:
+    pass
 import os
 import sys