Feat/showcase gallery expansion

README.md

@@ -137,43 +137,63 @@ python tutorials/multi_robot_3d_reachavoid.py
   <tr>
     <td align="center" width="33%">
       <img src="media/showcase/risk_aware_cvar.gif" width="100%" alt="Ellipsoidal-obstacle CBF"><br>
-      <sub><b>Ellipsoidal-obstacle CBF</b><br>Unicycle reach-goal with linear class-K</sub>
+      <sub><b>Ellipsoidal-obstacle CBF</b> <a href="scripts/render_showcase.py" title="Source: render_risk_aware_cvar">🔗</a><br>Unicycle reach-goal with linear class-K</sub>
     </td>
     <td align="center" width="33%">
       <img src="media/showcase/stochastic_cbf.gif" width="100%" alt="Stochastic CBF"><br>
-      <sub><b>Stochastic CBF (SDE)</b><br>Safety under Brownian disturbance</sub>
+      <sub><b>Stochastic CBF (SDE)</b> <a href="scripts/render_showcase.py" title="Source: render_stochastic_cbf">🔗</a><br>Safety under Brownian disturbance</sub>
     </td>
     <td align="center" width="33%">
       <img src="media/showcase/robust_cbf.gif" width="100%" alt="Robust CBF"><br>
-      <sub><b>Robust CBF</b><br>Worst-case bounded disturbance</sub>
+      <sub><b>Robust CBF</b> <a href="scripts/render_showcase.py" title="Source: render_robust_cbf">🔗</a><br>Worst-case bounded disturbance</sub>
     </td>
   </tr>
   <tr>
     <td align="center">
       <img src="media/showcase/mppi_rollouts.gif" width="100%" alt="MPPI rollouts"><br>
-      <sub><b>MPPI rollout sampling</b><br>Sampling-based planning</sub>
+      <sub><b>MPPI rollout sampling</b> <a href="examples/unicycle/reach_goal/mppi_cbf.py" title="Source: examples/unicycle/reach_goal/mppi_cbf.py">🔗</a><br>Sampling-based planning</sub>
     </td>
     <td align="center">
       <img src="media/showcase/mppi_stl.gif" width="100%" alt="MPPI reach-avoid"><br>
-      <sub><b>MPPI reach-avoid</b><br>Sampling-based planning with goal + obstacle cost</sub>
+      <sub><b>MPPI reach-avoid</b> <a href="scripts/render_showcase.py" title="Source: render_mppi_stl">🔗</a><br>Sampling-based planning with goal + obstacle cost</sub>
     </td>
     <td align="center">
       <img src="media/showcase/multi_robot_2d.gif" width="100%" alt="Multi-robot 2D coordination"><br>
-      <sub><b>Multi-robot 2D</b><br>Coordination via shared CBFs</sub>
+      <sub><b>Multi-robot 2D</b> <a href="scripts/render_showcase.py" title="Source: render_multi_robot_2d">🔗</a><br>Coordination via shared CBFs</sub>
     </td>
   </tr>
   <tr>
     <td align="center">
       <img src="media/showcase/fixed_wing_3d.gif" width="100%" alt="Fixed-wing aerial 3D"><br>
-      <sub><b>Fixed-wing aerial 3D</b><br>UAV reach-drop-point in 3D</sub>
+      <sub><b>Fixed-wing aerial 3D</b> <a href="scripts/render_showcase.py" title="Source: render_fixed_wing_3d">🔗</a><br>UAV reach-drop-point in 3D</sub>
     </td>
     <td align="center">
       <img src="media/showcase/pedestrian_head_on.gif" width="100%" alt="Pedestrian head-on"><br>
-      <sub><b>Pedestrian head-on</b><br>Dynamic-agent avoidance</sub>
+      <sub><b>Pedestrian head-on</b> <a href="examples/pedestrian/navigate_among_pedestrians/head_on.py" title="Source: examples/pedestrian/navigate_among_pedestrians/head_on.py">🔗</a><br>Dynamic-agent avoidance</sub>
     </td>
     <td align="center">
       <img src="media/showcase/ekf_estimation.gif" width="100%" alt="EKF state estimation"><br>
-      <sub><b>EKF state estimation</b><br>CBF over noisy estimates</sub>
+      <sub><b>EKF state estimation</b> <a href="examples/unicycle/reach_goal/ekf.py" title="Source: examples/unicycle/reach_goal/ekf.py">🔗</a><br>Unicycle reach-goal under measurement noise</sub>
+    </td>
+  </tr>
+  <tr>
+    <td align="center" width="33%">
+      <img src="media/showcase/van_der_pol_clf.gif" width="100%" alt="Van der Pol CLF"><br>
+      <sub><b>Van der Pol (CLF)</b> <a href="scripts/render_showcase.py" title="Source: render_van_der_pol_clf">🔗</a><br>Nonlinear regulation to the origin</sub>
+    </td>
+    <td align="center" width="33%">
+      <img src="media/showcase/mpc_double_integrator.gif" width="100%" alt="Model Predictive Control"><br>
+      <sub><b>Model Predictive Control</b> <a href="scripts/render_showcase.py" title="Source: render_mpc_double_integrator">🔗</a><br>Receding-horizon LTI tracking</sub>
+    </td>
+    <td align="center" width="33%">
+      <img src="media/showcase/quadrotor_6dof.gif" width="100%" alt="Quadrotor 6-DOF geometric tracking"><br>
+      <sub><b>Quadrotor 6-DOF</b> <a href="scripts/render_showcase.py" title="Source: render_quadrotor_6dof">🔗</a><br>Geometric SE(3) tracking + altitude CBF</sub>
+    </td>
+  </tr>
+  <tr>
+    <td align="center" colspan="3">
+      <img src="media/showcase/monte_carlo_safety.gif" width="45%" alt="Monte Carlo safety verification"><br>
+      <sub><b>Monte Carlo safety verification</b> <a href="scripts/render_showcase.py" title="Source: render_monte_carlo_safety">🔗</a><br>200 stochastic CBF rollouts (<code>jax.vmap</code>), live empirical risk</sub>
     </td>
   </tr>
 </table>

examples/unicycle/reach_goal/ekf.py

@@ -104,7 +104,8 @@ def dhdx(x):
         x_lim=(-5, 5),
         y_lim=(-5, 5),
         dt=dt,
-        title="System Behavior",
+        title="EKF State Estimation",
         save_animation=save,
         animation_filename="examples/unicycle/reach_goal/results/ekf_estimation.gif",
+        backend="matplotlib",
     )

examples/unicycle/reach_goal/mppi_cbf.py

@@ -219,8 +219,8 @@ def terminal_cost(state: Array, action: Array) -> Array:
         title="System Behavior (MPPI + CBF)",
         obstacles=obstacles,
         ellipsoids=ellipsoids,
-        save_animation=False,
-        animation_filename=file_path + "bh_mppi_cbf_control",
+        save_animation=save,
+        animation_filename=file_path + "mppi_rollouts.gif",
     )
 
 final_pos = x[-1, :2]