diff --git a/examples/continuous_orbit_manuevers.ipynb b/examples/continuous_orbit_manuevers.ipynb
index cbdcac3..8baf464 100644
--- a/examples/continuous_orbit_manuevers.ipynb
+++ b/examples/continuous_orbit_manuevers.ipynb
@@ -16,19 +16,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
+    "# %matplotlib qt  # Uncomment to use interactive plotting, may need `pip install PyQt5`\n",
+    "\n",
     "import numpy as np\n",
     "from functools import partial\n",
-    "from bsk_rl import act, obs, sats, ConstellationTasking\n",
+    "from bsk_rl import act, obs, sats, ConstellationTasking, comm\n",
     "from bsk_rl.sim import dyn, fsw\n",
     "from bsk_rl.utils.orbital import relative_to_chief, random_orbit\n",
     "from bsk_rl.scene import FibonacciSphereRSOPoints\n",
     "from bsk_rl.data import RSOInspectionReward\n",
     "\n",
     "from Basilisk.architecture import bskLogging\n",
+    "from Basilisk.utilities.RigidBodyKinematics import MRP2C\n",
     "\n",
     "bskLogging.setDefaultLogLevel(bskLogging.BSK_WARNING)\n"
    ]
@@ -48,7 +51,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -57,7 +60,7 @@
     "\n",
     "class TumbleSat(sats.Satellite):\n",
     "    observation_spec = [\n",
-    "        obs.SatProperties(dict(prop=\"r_BN_N\")),\n",
+    "        obs.SatProperties(dict(prop=\"r_BN_N\"), dict(prop=\"sigma_BN\")),\n",
     "    ]\n",
     "    action_spec = [act.Drift()]\n",
     "    dyn_type = types.new_class(\"Dyn\", (dyn.ConjunctionDynModel, dyn.RSODynModel))\n",
@@ -102,18 +105,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[90;3m2024-12-12 10:59:43,536 \u001b[0m\u001b[m                               \u001b[0m\u001b[93mWARNING    \u001b[0m\u001b[93mCreating logger for new env on PID=54499. Old environments in process may now log times incorrectly.\u001b[0m\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
        "{'Tumbler': Discrete(1),\n",
-       " 'Thrust-1': Box([-100. -100. -100.    0.], [100. 100. 100.  inf], (4,), float32),\n",
-       " 'Thrust-2': Box([-100. -100. -100.    0.], [100. 100. 100.  inf], (4,), float32)}"
+       " 'Thrust-1': Box([-100. -100. -100.    0.], [100. 100. 100.  inf], (4,), float32)}"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -133,23 +142,31 @@
     "        TumbleSat(\n",
     "            \"Tumbler\",\n",
     "            obs_type=dict,\n",
-    "            sat_args=dict(omega_init=np.zeros(3)),\n",
+    "            sat_args=dict(\n",
+    "                # sigma_init=np.zeros(3),\n",
+    "                # omega_init=np.zeros(3),\n",
+    "            ),\n",
     "        ),\n",
     "        ThrustSat(\"Thrust-1\", obs_type=dict, sat_args=scanner_sat_args),\n",
-    "        ThrustSat(\"Thrust-2\", obs_type=dict, sat_args=scanner_sat_args),\n",
+    "        # ThrustSat(\"Thrust-2\", obs_type=dict, sat_args=scanner_sat_args),\n",
     "    ],\n",
     "    sat_arg_randomizer=relative_to_chief(\n",
     "        chief_name=\"Tumbler\",\n",
-    "        chief_orbit=partial(random_orbit, i=None),\n",
+    "        chief_orbit=partial(random_orbit, i=0, Omega=0, omega=0, f=0),\n",
     "        deputy_relative_state={\n",
-    "            \"Thrust-1\": np.array([500, 0, 0, 0, 0, 0]),\n",
-    "            \"Thrust-2\": np.array([-500, 0, 0, 0, 0, 0]),\n",
+    "            \"Thrust-1\": np.array([50, 0, 0, 0, 0, 0]),\n",
+    "            # \"Thrust-2\": np.array([-50, 0, 0, 0, 0, 0]),\n",
     "        },\n",
     "    ),\n",
-    "    scenario=FibonacciSphereRSOPoints(n_points=200),\n",
+    "    scenario=FibonacciSphereRSOPoints(\n",
+    "        n_points=500,\n",
+    "        radius=10,\n",
+    "        theta_min=np.radians(30),\n",
+    "    ),\n",
+    "    # communicator=comm.LOSCommunication(),\n",
     "    rewarder=RSOInspectionReward(),\n",
     "    time_limit=5700.0 * 3,\n",
-    "    log_level=\"WARNING\",\n",
+    "    log_level=\"INFO\",\n",
     ")\n",
     "env.action_spaces"
    ]
@@ -165,15 +182,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
+     "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[91mBSK_ERROR\u001b[0m: Error: In the locationPointing module no target messages were not connected.\n",
-      "\u001b[91mBSK_ERROR\u001b[0m: Error: In the locationPointing module no target messages were not connected.\n"
+      "\u001b[90;3m2024-12-12 10:59:43,854 \u001b[0m\u001b[mgym                            \u001b[0m\u001b[mINFO       \u001b[0m\u001b[mResetting environment with seed=281930216\u001b[0m\n",
+      "\u001b[90;3m2024-12-12 10:59:43,970 \u001b[0m\u001b[36msats.satellite.Thrust-1.FSW    \u001b[0m\u001b[mINFO       \u001b[0m\u001b[33m<0.00> \u001b[0m\u001b[36mThrust-1: \u001b[0m\u001b[m<Basilisk.architecture.messaging.NavTransMsgPayload.NavTransMsg_C; proxy of <Swig Object of type 'NavTransMsg_C *' at 0x32e667330> >\u001b[0m\n",
+      "\u001b[90;3m2024-12-12 10:59:44,043 \u001b[0m\u001b[mgym                            \u001b[0m\u001b[mINFO       \u001b[0m\u001b[33m<0.00> \u001b[0m\u001b[mEnvironment reset\u001b[0m\n"
      ]
     }
    ],
@@ -193,237 +211,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[90;3m2024-12-07 19:21:47,414 \u001b[0m\u001b[36msats.satellite.Tumbler         \u001b[0m\u001b[93mWARNING    \u001b[0m\u001b[33m<600.00> \u001b[0m\u001b[36mTumbler: \u001b[0m\u001b[93mRequires retasking but received no task.\u001b[0m\n"
+      "\u001b[90;3m2024-12-12 10:59:44,049 \u001b[0m\u001b[mgym                            \u001b[0m\u001b[mINFO       \u001b[0m\u001b[33m<0.00> \u001b[0m\u001b[93;1m=== STARTING STEP ===\u001b[0m\n",
+      "\u001b[90;3m2024-12-12 10:59:44,050 \u001b[0m\u001b[92msats.satellite.Tumbler         \u001b[0m\u001b[93mWARNING    \u001b[0m\u001b[33m<0.00> \u001b[0m\u001b[92mTumbler: \u001b[0m\u001b[93mRequires retasking but received no task.\u001b[0m\n",
+      "\u001b[90;3m2024-12-12 10:59:44,051 \u001b[0m\u001b[36msats.satellite.Thrust-1        \u001b[0m\u001b[mINFO       \u001b[0m\u001b[33m<0.00> \u001b[0m\u001b[36mThrust-1: \u001b[0m\u001b[mThrusting with inertial dV [0 0 0] with 1000 second drift.\u001b[0m\n",
+      "\u001b[90;3m2024-12-12 10:59:44,052 \u001b[0m\u001b[36msats.satellite.Thrust-1        \u001b[0m\u001b[mINFO       \u001b[0m\u001b[33m<0.00> \u001b[0m\u001b[36mThrust-1: \u001b[0m\u001b[msetting timed terminal event at 1000.0\u001b[0m\n",
+      "\u001b[90;3m2024-12-12 10:59:44,052 \u001b[0m\u001b[36msats.satellite.Thrust-1        \u001b[0m\u001b[mINFO       \u001b[0m\u001b[33m<0.00> \u001b[0m\u001b[36mThrust-1: \u001b[0m\u001b[mFSW action action_inspect_rso activated.\u001b[0m\n",
+      "\u001b[90;3m2024-12-12 10:59:44,311 \u001b[0m\u001b[36msats.satellite.Thrust-1        \u001b[0m\u001b[mINFO       \u001b[0m\u001b[33m<1000.00> \u001b[0m\u001b[36mThrust-1: \u001b[0m\u001b[mtimed termination at 1000.0 \u001b[0m\n",
+      "\u001b[90;3m2024-12-12 10:59:44,959 \u001b[0m\u001b[36msats.satellite.Thrust-1        \u001b[0m\u001b[mINFO       \u001b[0m\u001b[33m<1000.00> \u001b[0m\u001b[36mThrust-1: \u001b[0m\u001b[mInspected 44 points this step\u001b[0m\n",
+      "\u001b[90;3m2024-12-12 10:59:44,959 \u001b[0m\u001b[mdata.base                      \u001b[0m\u001b[mINFO       \u001b[0m\u001b[33m<1000.00> \u001b[0m\u001b[mData reward: {}\u001b[0m\n",
+      "\u001b[90;3m2024-12-12 10:59:44,959 \u001b[0m\u001b[92msats.satellite.Tumbler         \u001b[0m\u001b[mINFO       \u001b[0m\u001b[33m<1000.00> \u001b[0m\u001b[92mTumbler: \u001b[0m\u001b[mSatellite Tumbler requires retasking\u001b[0m\n",
+      "\u001b[90;3m2024-12-12 10:59:44,960 \u001b[0m\u001b[36msats.satellite.Thrust-1        \u001b[0m\u001b[mINFO       \u001b[0m\u001b[33m<1000.00> \u001b[0m\u001b[36mThrust-1: \u001b[0m\u001b[mSatellite Thrust-1 requires retasking\u001b[0m\n",
+      "\u001b[90;3m2024-12-12 10:59:44,961 \u001b[0m\u001b[mgym                            \u001b[0m\u001b[mINFO       \u001b[0m\u001b[33m<1000.00> \u001b[0m\u001b[mStep reward: {}\u001b[0m\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
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+      "[ 3.05834745e+06  6.14678990e+06 -3.30911937e+01]\n",
+      "[ 3.05846436e+06  6.14688063e+06 -3.30899829e+01]\n"
      ]
-    },
-    {
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",
-      "text/plain": [
-       "<Figure size 575x250 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
     }
    ],
    "source": [
     "for _ in range(1):\n",
     "    actions = {\n",
-    "        \"Thrust-1\": np.array([0, 0, 0, 60]),\n",
-    "        \"Thrust-2\": np.array([0, 0, 0, 60]),\n",
+    "        \"Thrust-1\": np.array([0, 0, 0, 1000]),\n",
+    "        # \"Thrust-2\": np.array([0, 0, 0, 1]),\n",
     "    }\n",
     "    # for sat in env.satellites:\n",
     "    #     if sat.requires_retasking:\n",
@@ -439,10 +260,17 @@
     "    # print(env.satellites[1].data_store.data.point_inspect_status)\n",
     "    # print(\"storage:\", observation[\"Thrust-1\"][\"sat_props\"][\"storage_level_fraction\"])\n",
     "\n",
+    "BN = MRP2C(observation[\"Tumbler\"][\"sat_props\"][\"sigma_BN\"])\n",
+    "\n",
     "fig, ax = plt.subplots(1, 1, subplot_kw=dict(projection=\"3d\"))\n",
     "for point, inspected in env.satellites[1].data_store.data.point_inspect_status.items():\n",
     "    # print(point, inspected)\n",
-    "    ax.scatter(*point.r_PB_B, color=\"tab:green\" if inspected else \"tab:red\")"
+    "    ax.scatter(*(BN.T @ point.r_PB_B), color=\"tab:green\" if inspected else \"tab:red\")\n",
+    "\n",
+    "# ax.scatter(\n",
+    "#     *observation[\"Thrust-1\"][\"rel_props\"][\"r_DC_N\"], color=\"tab:blue\", marker=\"x\"\n",
+    "# )\n",
+    "ax.set_aspect(\"equal\")"
    ]
   }
  ],
diff --git a/src/bsk_rl/data/rso_data.py b/src/bsk_rl/data/rso_data.py
index d3c849c..5c3dec3 100644
--- a/src/bsk_rl/data/rso_data.py
+++ b/src/bsk_rl/data/rso_data.py
@@ -86,9 +86,9 @@ def get_log_state(self) -> list[list[bool]]:
 
         inspected_logs = []
         for recorder in self.point_access_recorders:
-            # inspected = np.logical_and(imaging_req, recorder.hasAccess)
-            inspected = recorder.hasAccess
-            inspected_logs.append(list(inspected))
+            inspected = np.logical_and(imaging_req, recorder.hasAccess)
+            # inspected = recorder.hasAccess
+            inspected_logs.append(list(np.array(inspected)))
 
         self.clear_recorders()
 
@@ -103,7 +103,6 @@ def compare_log_states(self, _, inspected_logs) -> Data:
             self.data.point_inspect_status.keys(), inspected_logs
         ):
             if any(log):
-                print(log)
                 point_inspect_status[rso_point] = True
 
         if len(point_inspect_status) > 0:
diff --git a/src/bsk_rl/gym.py b/src/bsk_rl/gym.py
index cf5a5ea..3f12dac 100644
--- a/src/bsk_rl/gym.py
+++ b/src/bsk_rl/gym.py
@@ -281,6 +281,12 @@ def reset(
             time_limit=self.time_limit,
         )
 
+        self.scenario.reset_during_sim_init()
+        self.rewarder.reset_during_sim_init()
+        self.communicator.reset_during_sim_init()
+
+        self.simulator.finish_init()
+
         self.scenario.reset_post_sim_init()
         self.rewarder.reset_post_sim_init()
         self.communicator.reset_post_sim_init()
diff --git a/src/bsk_rl/scene/rso_points.py b/src/bsk_rl/scene/rso_points.py
index 50cc8c1..a925302 100644
--- a/src/bsk_rl/scene/rso_points.py
+++ b/src/bsk_rl/scene/rso_points.py
@@ -7,12 +7,10 @@
 
 import numpy as np
 import pandas as pd
-from Basilisk.utilities import orbitalMotion
 
 from bsk_rl.scene import Scenario
 from bsk_rl.sim.dyn import RSODynModel, RSOImagingDynModel
 from bsk_rl.sim.fsw import RSOImagingFSWModel
-from bsk_rl.utils.orbital import lla2ecef
 
 if TYPE_CHECKING:  # pragma: no cover
     from bsk_rl.data.base import Data
@@ -40,11 +38,9 @@ def reset_overwrite_previous(self) -> None:
 
     def reset_pre_sim_init(self) -> None:
         self.rso_points = self.generate_points()
-        return super().reset_pre_sim_init()
 
-    def reset_post_sim_init(self) -> None:
         # Check for RSOs and observers
-        rsos = [sat for sat in self.satellites if isinstance(sat.dynamics, RSODynModel)]
+        rsos = [sat for sat in self.satellites if issubclass(sat.dyn_type, RSODynModel)]
         if len(rsos) == 0:
             logger.warning("No RSODynModel satellites found in scenario.")
             return
@@ -54,12 +50,15 @@ def reset_post_sim_init(self) -> None:
         self.observers = [
             sat
             for sat in self.satellites
-            if isinstance(sat.dynamics, RSOImagingDynModel)
+            if issubclass(sat.dyn_type, RSOImagingDynModel)
         ]
         if len(self.observers) == 0:
             logger.warning("No RSOImagingDynModel satellites found in scenario.")
             return
 
+        return super().reset_pre_sim_init()
+
+    def reset_during_sim_init(self) -> None:
         # Add points to dynamics and fsw of RSO
         assert isinstance(self.rso.dynamics, RSODynModel)
         logger.debug("Adding inspection points to RSO and observers")
diff --git a/src/bsk_rl/sim/dyn.py b/src/bsk_rl/sim/dyn.py
index 0d011f3..109d684 100644
--- a/src/bsk_rl/sim/dyn.py
+++ b/src/bsk_rl/sim/dyn.py
@@ -1252,22 +1252,32 @@ def __init__(self, *args, **kwargs) -> None:
 
     def _setup_dynamics_objects(self, **kwargs) -> None:
         super()._setup_dynamics_objects(**kwargs)
+
+        rso_dyn_proc_name = "RSODynProcess"
+        self.rso_dyn_proc = self.simulator.CreateNewProcess(rso_dyn_proc_name, 1)
+        self.rso_task_name = "RSODynTask"
+        self.rso_dyn_proc.addTask(
+            self.simulator.CreateNewTask(
+                self.rso_task_name, macros.sec2nano(self.dyn_rate)
+            )
+        )
+
         self.rso_points = []
 
     def add_rso_point(self, r_LB_B, aHat_B, theta, range):
         rso_point_model = spacecraftLocation.SpacecraftLocation()
         rso_point_model.primaryScStateInMsg.subscribeTo(self.scObject.scStateOutMsg)
-        rso_point_model.planetInMsg.subscribeTo(
-            self.world.gravFactory.spiceObject.planetStateOutMsgs[self.world.body_index]
-        )
-        rso_point_model.rEquator = self.simulator.world.planet.radEquator
-        rso_point_model.rPolar = self.simulator.world.planet.radEquator * 0.98
+        # rso_point_model.planetInMsg.subscribeTo(
+        #     self.world.gravFactory.spiceObject.planetStateOutMsgs[self.world.body_index]
+        # )
+        rso_point_model.rEquator = 1.0  # self.simulator.world.planet.radEquator
+        rso_point_model.rPolar = 1.0  # self.simulator.world.planet.radEquator * 0.98
         rso_point_model.r_LB_B = r_LB_B
         rso_point_model.aHat_B = aHat_B
         rso_point_model.theta = theta
         rso_point_model.maximumRange = range
         self.simulator.AddModelToTask(
-            self.task_name, rso_point_model, ModelPriority=2000
+            self.rso_task_name, rso_point_model, ModelPriority=1
         )
 
         self.rso_points.append(rso_point_model)
diff --git a/src/bsk_rl/sim/simulator.py b/src/bsk_rl/sim/simulator.py
index 09d5834..249a2fc 100644
--- a/src/bsk_rl/sim/simulator.py
+++ b/src/bsk_rl/sim/simulator.py
@@ -57,6 +57,8 @@ def __init__(
             self.dynamics_list[satellite.name] = satellite.set_dynamics(self.sim_rate)
             self.fsw_list[satellite.name] = satellite.set_fsw(self.sim_rate)
 
+    def finish_init(self) -> None:
+        """Finish simulator initialization."""
         self.InitializeSimulation()
         self.ConfigureStopTime(0)
         self.ExecuteSimulation()
diff --git a/src/bsk_rl/utils/functional.py b/src/bsk_rl/utils/functional.py
index 9b3dbd7..3aceb95 100644
--- a/src/bsk_rl/utils/functional.py
+++ b/src/bsk_rl/utils/functional.py
@@ -200,6 +200,10 @@ def reset_pre_sim_init(self) -> None:
         """Reset before simulator initialization."""
         pass
 
+    def reset_during_sim_init(self) -> None:
+        """Reset after simulator models have been created but before the simulator is initialized."""
+        pass
+
     def reset_post_sim_init(self) -> None:
         """Reset after simulator initialization."""
         pass