Examples

Selected example scripts. Check out more in examples/

State control

A minimal demo showing how to use the Sim API at a very high level: create a Sim, send simple position commands and step the simulation. Useful to get started with high-level position/setpoint control.

python examples/change_pos.py

Cameras & RGBD

Shows how to obtain RGB and depth frames from the renderer. Demonstrates offscreen capture via sim.render(), retrieving image arrays for perception or visual‑in‑the‑loop controllers, and saving sequences (GIFs).

python examples/cameras.py

RGB Image Depth Image

cameras

Contacts & collision model

Demonstrates how to query contact information from the simulation and how to switch collision geometry types (e.g., sphere → box) for higher‑fidelity contact modeling. Useful for debugging collisions or when more accurate contact checks are required.

python examples/contacts.py

contact_sphere contact_box

LED deck & materials

Illustrates how to activate and control the LED deck and other drone material colors at runtime for visualization and debugging.

python examples/led_deck.py

led_deck

Randomization

Shows how to add reset‑time randomization: initial position/quaternion randomization, mass/inertia perturbations and other properties that should vary between episodes. The example demonstrates how to register reset randomizers and how to persist different initial conditions across runs.

Run:

python examples/randomize.py

Disturbance

Demonstrates step‑time disturbances inserted into the step pipeline (external forces/torques, actuator noise, etc.). The example (examples/disturbance.py) shows how to insert a disturbance function into sim.step_pipeline, compare disturbed vs undisturbed runs and optionally plot the resulting trajectories.

Run:

python examples/disturbance.py

Figure‑8 / RL environment

A scripted figure‑8 environment intended for evaluation or as a training target. The example shows how to create vectorized envs, apply the NormalizeActions wrapper and step/render the environment. It does not include any agent implementations — integrate the environment with your preferred RL training code (Stable Baselines3, RLlib, custom JAX trainers, etc.).

Run:

python examples/figure8.py

For API details and configuration options referenced by these examples, see the API Reference and Usage.