Domino system-ID tasks: reach-limited min-block (friction) + heavy-block obstacle (mass)

.predicators_pylintrc

@@ -10,7 +10,7 @@ extension-pkg-whitelist=numpy,pybullet,torch,tensorflow,pyrealsense2
 ignore=CVS
 
 # Add paths to the blacklist.
-ignore-paths=predicators/envs/assets,predicators/third_party,venv
+ignore-paths=predicators/envs/assets,predicators/third_party,venv,docs
 
 # Add files or directories matching the regex patterns to the blacklist. The
 # regex matches against base names, not paths.

docs/envs/assets/domino_min_block/make_anatomy_fig.py

@@ -0,0 +1,80 @@
+"""Schematic: min-block task anatomy — init, calibrated plan, miscalibrated
+plan. Pure drawing (numbers match the measured reaches)."""
+import matplotlib
+
+matplotlib.use("Agg")
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+import numpy as np
+from matplotlib.patches import FancyArrowPatch, Rectangle
+
+W, D = 0.07, 0.015  # domino width (perp to chain) x depth (along chain)
+SPAN = 0.26
+TRUE_REACH, BELIEVED_REACH = 0.11, 0.16
+
+
+def block(ax, x, y, color, label=None):
+    ax.add_patch(
+        Rectangle((x - D / 2, y - W / 2), D, W, facecolor=color,
+                  edgecolor="k", lw=1.2, zorder=3))
+    if label:
+        ax.text(x, y - W / 2 - 0.03, label, ha="center", va="top", fontsize=9)
+
+
+def gap_arrow(ax, x0, x1, y, txt, color):
+    ax.add_patch(
+        FancyArrowPatch((x0 + D / 2, y), (x1 - D / 2, y), arrowstyle="<->",
+                        color=color, mutation_scale=10, lw=1.4, zorder=2))
+    ax.text((x0 + x1) / 2, y + 0.045, txt, ha="center", fontsize=9,
+            color=color)
+
+
+fig, axes = plt.subplots(1, 3, figsize=(13, 3.2))
+
+# ── Panel 1: the task ────────────────────────────────────────────
+ax = axes[0]
+block(ax, 0.0, 0.0, "#7fc97f", "start\n(push me)")
+block(ax, SPAN, 0.0, "#c599c5", "target\n(topple me)")
+gap_arrow(ax, 0.0, SPAN, 0.0, f"span {SPAN} m", "k")
+for i, bx in enumerate((0.04, 0.10, 0.16, 0.22)):
+    block(ax, bx, -0.16, "#7fb2d9")
+ax.text(0.13, -0.235, "4 staged blues (place as few as possible)",
+        ha="center", fontsize=9, color="#33658a")
+ax.set_title("Task: topple target with ≤ K* blues", fontsize=11)
+
+# ── Panel 2: calibrated plan (true reach 0.11 → K*=2) ────────────
+ax = axes[1]
+block(ax, 0.0, 0.0, "#7fc97f")
+g = SPAN / 3
+for i in (1, 2):
+    block(ax, i * g, 0.0, "#7fb2d9")
+block(ax, SPAN, 0.0, "#c599c5")
+gap_arrow(ax, 0.0, g, 0.0, f"{g:.3f} ≤ 0.11 ✓", "#1a7a1a")
+ax.text(SPAN / 2, -0.19, "true reach 0.11 → K* = 2 blues\ntopples ✓  uses 2 ≤ K* ✓  REWARD",
+        ha="center", fontsize=10, color="#1a7a1a")
+ax.set_title("Calibrated model (friction 0.1)", fontsize=11)
+
+# ── Panel 3: miscalibrated plan (believed reach 0.16 → 1 blue) ───
+ax = axes[2]
+block(ax, 0.0, 0.0, "#7fc97f")
+block(ax, SPAN / 2, 0.0, "#7fb2d9")
+block(ax, SPAN, 0.0, "#c599c5")
+gap_arrow(ax, 0.0, SPAN / 2, 0.0, f"{SPAN/2:.2f} ≤ 0.16 ?", "#b3541e")
+ax.text(SPAN * 0.75, 0.09, "✗ chain dies\n(0.13 > 0.11 real reach)",
+        ha="center", fontsize=10, color="#a01515")
+ax.text(SPAN / 2, -0.19,
+        "believed reach 0.16 → plans 1 blue\nvalidates in ITS sim, fails in real",
+        ha="center", fontsize=10, color="#a01515")
+ax.set_title("Miscalibrated model (believes 0.5)", fontsize=11)
+
+for ax in axes:
+    ax.set_xlim(-0.09, 0.36)
+    ax.set_ylim(-0.28, 0.17)
+    ax.set_aspect("equal")
+    ax.axis("off")
+
+fig.tight_layout()
+out = str(Path(__file__).parent / "task_anatomy.png")
+fig.savefig(out, dpi=140, bbox_inches="tight")
+print("saved", out)