feat(sim): add RotorPy simulator support (#27116)

* Add rotorpy simulator and integrate with main simulator script

* docs: add rotorpy simulator instructions

* docs(update): subedit

* docs: address RotorPy review comments

---------

Co-authored-by: Davide Iafrate <dvde.iafrate98@gmail.com>
Co-authored-by: Ramon Roche <mrpollo@gmail.com>
Co-authored-by: Hamish Willee <hamishwillee@gmail.com>

docs/en/sim_rotorpy/index.md

@@ -0,0 +1,96 @@
+# RotorPy Simulation
+
+:::warning
+This simulator is [community supported and maintained](../simulation/community_supported_simulators.md).
+It may or may not work with current versions of PX4.
+
+See [Toolchain Installation](../dev_setup/dev_env.md) for information about the environments and tools supported by the core development team.
+:::
+
+RotorPy is a Python-based multirotor simulation environment with [aerodynamic wrenches](https://arxiv.org/abs/2306.04485), useful for education and research in estimation, planning, and control for UAVs.
+It provides stand-alone classes and a [Gymnasium environment](https://gymnasium.farama.org/).
+
+<lite-youtube videoid="L8-QZgc6Vwk" title="Demo of PX4 with RotorPy simulator"/>
+
+## Why Use RotorPy?
+
+RotorPy simulates the aerodynamic forces and moments acting on a multirotor, along with actuator limits, sensor noise, wind, and obstacles.
+This makes it useful when you want to test estimation, planning, or control algorithms against more realistic vehicle dynamics than a simple point-mass or kinematic simulation.
+
+The Gymnasium interface is useful for reinforcement learning and other Python-based research workflows.
+It lets you connect policies and learning pipelines to a PX4-controlled multirotor simulation without rewriting them around PX4-specific APIs.
+
+## Installation
+
+RotorPy can be installed using `pip`:
+
+```sh
+pip install rotorpy[px4]
+```
+
+To install other tagged versions, see [`pyproject.toml`](https://github.com/spencerfolk/rotorpy/blob/main/pyproject.toml).
+
+## Running the Simulation
+
+This example will allow you to control the quadrotor through QGroundControl.
+
+::: tip
+If instead you want RotorPy to take control of the drone you can pass the `autopilot_controller=False` argument to the `PX4Multirotor` constructor when instantiating it.
+This can be useful to test perception pipelines, since the environment is controlled through RotorPy's own controllers.
+:::
+
+First you need to build the SITL binary by setting up the toolchain and running:
+
+```sh
+make px4_sitl
+```
+
+Then run the PX4 SITL binary with the command:
+
+```sh
+PX4SIMULATOR=rotorpy PX4_SYS_AUTOSTART=10040 ./build/px4_sitl_default/bin/px4
+```
+
+Start the `example/px4_basic_example.py`, available [here](https://github.com/spencerfolk/rotorpy/blob/main/examples/basic_usage_px4.py) and referenced in the code below:
+
+```python
+# test_px4_sitl.py
+
+from rotorpy.environments               import Environment
+from rotorpy.trajectories.circular_traj import ThreeDCircularTraj
+from rotorpy.vehicles.px4_multirotor    import PX4Multirotor
+from rotorpy.vehicles.px4_sihsim_quadx_params import quad_params as sihsim_quadx
+from rotorpy.controllers.quadrotor_control import SE3Control
+from rotorpy.trajectories.hover_traj    import HoverTraj
+
+import numpy as np
+
+circular_trajectory = ThreeDCircularTraj(radius=np.array([1,1,0]))
+hover_trajectory = HoverTraj(x0=np.array([0, 0, 5]))
+
+def main():
+    vehicle    = PX4Multirotor(sihsim_quadx, enable_ground=True)
+    controller = SE3Control(sihsim_quadx)
+
+    env = Environment(
+        vehicle    = vehicle,
+        controller = controller,
+        trajectory = circular_trajectory,
+        sim_rate   = 100,
+    )
+    results = env.run(
+        t_final      = 60,
+        use_mocap=False,
+        plot_mocap=False,
+        plot_estimator=False,
+        plot_imu=False,
+        plot         = True,
+        animate_bool = False,
+        verbose      = True,
+    )
+
+    print("Done—PX4 SITL ran for", len(results["time"]), "steps")
+
+if __name__ == '__main__':
+    main()
+```