Update inputs: engineering/humanoid_velocity_tracking_policy/base

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tasks/engineering/humanoid_velocity_tracking_policy/base/input/PROPRIO_SPEC.md

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+# Proprioceptive State Vector Spec
+
+The `obs["state"]` tensor passed to `Policy.inference` is a fixed-order
+concatenation of six terms, totalling **S = 78**.  The commanded velocity
+(`[vx, vy, omega]`, 3-dim) is delivered separately via `obs["command"]`
+and is **NOT** part of `S`.
+
+Ordering matches the eval env's observation group, minus
+`velocity_commands` (which is pulled out into `obs["command"]`).  If
+your submission recombines `command` and `state` into a single MLP
+input, place `command` at the position your training used. The
+reference training order is `[base_lin_vel, base_ang_vel,
+projected_gravity, command, joint_pos_rel, joint_vel, last_action]`,
+so `command` is inserted after `projected_gravity` at state offset 9.
+
+| Index range | Term              | Dim | Units / frame                                      |
+|-------------|-------------------|-----|----------------------------------------------------|
+| `[0:3]`     | `base_lin_vel`    | 3   | m/s, base frame (torso)                            |
+| `[3:6]`     | `base_ang_vel`    | 3   | rad/s, base frame                                  |
+| `[6:9]`     | `projected_gravity` | 3 | unit gravity vector in base frame (z ≈ −1 upright) |
+| `[9:32]`    | `joint_pos_rel`   | 23  | rad; `q − q_default`, URDF revolute order          |
+| `[32:55]`   | `joint_vel`       | 23  | rad/s, URDF revolute order                         |
+| `[55:78]`   | `last_action`     | 23  | raw policy output (pre-scale, pre-offset)          |
+
+**Total `S` = 78.**
+
+## Joint ordering (A = 23)
+
+Revolute joint order as declared in `assets/robot.urdf`; Isaac Lab
+preserves this ordering via `env.scene["robot"].joint_names`:
+
+```
+ 0  AAHead_yaw
+ 1  Head_pitch
+ 2  Left_Shoulder_Pitch
+ 3  Right_Shoulder_Pitch
+ 4  Waist
+ 5  Left_Shoulder_Roll
+ 6  Right_Shoulder_Roll
+ 7  Left_Hip_Pitch
+ 8  Right_Hip_Pitch
+ 9  Left_Elbow_Pitch
+10  Right_Elbow_Pitch
+11  Left_Hip_Roll
+12  Right_Hip_Roll
+13  Left_Elbow_Yaw
+14  Right_Elbow_Yaw
+15  Left_Hip_Yaw
+16  Right_Hip_Yaw
+17  Left_Knee_Pitch
+18  Right_Knee_Pitch
+19  Left_Ankle_Pitch
+20  Right_Ankle_Pitch
+21  Left_Ankle_Roll
+22  Right_Ankle_Roll
+```
+
+The three columns `joint_pos_rel`, `joint_vel`, and `last_action` all
+follow this order.  Isaac Lab orders DoFs breadth-first from the
+articulation root, so the per-body order can look unintuitive — but the
+same articulation is used at train and eval time, so submissions can
+rely on the runtime order matching this spec.  The authoritative
+runtime order comes from ``env.scene["robot"].joint_names``; print it
+on first call if you want to confirm.
+
+## Notes
+
+- All angles are radians; linear quantities are in SI units (m, m/s).
+- `base frame` means the `Trunk` link frame (URDF root rigid body).
+- `projected_gravity` is the gravity vector rotated into the base frame
+  and normalised, so `z ≈ −1` when upright.
+- `joint_pos_rel` is `q − q_default`; the default pose is the one in
+  `assets/articulation_cfg.py:_DEFAULT_JOINT_POS` (arms tucked with
+  shoulder roll ±1.3 + shoulder pitch 0.2 + elbow yaw ±0.5, waist and
+  head at 0, hip pitch −0.20, knee pitch 0.40, ankle pitch −0.25, rest
+  0).
+- `last_action` is the *raw* action the policy emitted at the previous
+  step (before the env multiplies by `ACTION_SCALE = 0.5` and adds the
+  default offset).
+- The baseline training env injects additive uniform noise on the
+  proprio terms during rollout; the eval env disables that noise so the
+  `obs["state"]` you see is the clean state.  If your training relied on
+  frame stacking / history, reproduce that buffering inside
+  `Policy.inference` — the eval env provides only the single-step obs.

tasks/engineering/humanoid_velocity_tracking_policy/base/input/SUCCESS.md

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+# Verifying Success
+
+Strict, machine-checkable rules for the automated grader. Each gate is
+pass/fail with no subjective interpretation.
+
+## 1. Submission structure (hard gate — any failure = reject)
+
+- Submission contains exactly two files at the expected paths:
+  `policy.py` and `checkpoint.pt`.
+- `policy.py` imports cleanly under the Isaac Lab v2.3.2 / Isaac Sim 5.1.0
+  environment with **no extra `pip install`**. Disallowed prefixes
+  (regex, whole-word): `rsl_rl\b`, `stable_baselines3\b`, `sb3\b`,
+  `ray\b`, `hydra\b`.
+- `policy.py` defines a top-level class `Policy` whose
+  `__init__(checkpoint_path: str, device: str)` returns in ≤ 60 s on
+  the grading host.
+- `checkpoint.pt` is loadable by `Policy.__init__` — no download
+  attempts, no filesystem writes outside the working dir, no network
+  calls.
+
+## 2. API contract (hard gate)
+
+Invoke `Policy.inference({"command": C, "state": S})` once with a
+smoke-test batch `N=4` on CUDA. The return value must satisfy, exactly:
+
+- `isinstance(out, dict)` and `set(out.keys()) == {"action"}`.
+- `out["action"].shape == (N, 23)`, `dtype == torch.float32`,
+  `device == C.device`.
+- No NaNs, no Infs, `|action|.max() <= 100.0` (sanity clip — not a
+  performance gate).
+- Call is idempotent: two back-to-back inferences on identical input
+  produce tensors with `torch.allclose(a, b, atol=1e-6)`.
+
+## 3. Evaluation protocol (reference command, byte-identical)
+
+```bash
+python eval/run_eval.py \
+  --policy <submission>/policy.py \
+  --checkpoint <submission>/checkpoint.pt \
+  --seeds 0 1 2 3 4 5 6 7 8 9 \
+  --num_envs 64 --rollout_seconds 20.0 \
+  --device cuda --results_path results.json
+```
+
+- Grader runs this command twice back-to-back. Both runs must emit a
+  valid `results.json` containing the fields `lin_vel_rmse_xy`,
+  `ang_vel_mae_z`, `fall_rate`, `per_seed`.
+- **Determinism check:** per-seed metrics across the two runs must
+  agree to `atol=1e-4` (floating-point tolerance). Larger drift =
+  reject (submission introduced non-determinism, e.g. uninitialised
+  buffer, dropout in eval, stochastic sampling).
+
+## 4. Numerical acceptance (primary score)
+
+Let `L = lin_vel_rmse_xy` (m/s), `A = ang_vel_mae_z` (rad/s),
+`F = fall_rate` — all computed as the 10-seed mean from the reference
+command above.
+
+- **Fall gate (hard reject):** `F > 0.5` → fail, regardless of `L + A`.
+- **Primary score:** `S = L + A` (lower is better).
+- **Tiebreaker 1:** `F` (lower wins).
+- **Tiebreaker 2:** `L` alone (lower wins) — used only if `S` and `F`
+  tie to 4 decimals.
+
+## 5. Baseline-relative pass bands (only if an absolute pass/fail is required)
+
+Reference baseline: `S_base = 0.3324 + 0.1850 = 0.5174`, `F_base = 0.0`.
+
+| Band | Condition |
+|---|---|
+| **Pass** | `F <= 0.05` **and** `S <= 0.5174 * 1.10` (i.e. `S <= 0.5691`) |
+| **Strong pass** | `F <= 0.01` **and** `S <= 0.5174` |
+| **Fail** | any other outcome |
+
+## 6. Comparison arithmetic (leaves no room for subjectivity)
+
+- All metrics are rounded to **4 decimal places** before comparison
+  (banker's rounding, `numpy.round`).
+- Ranking comparisons use the rounded values; ties at that precision
+  fall through to the next tiebreaker in §4.
+- `per_seed` arrays are aligned by seed index, not by order — the
+  grader reads `results["per_seed"]["seeds"]` as the key.
+
+## 7. Resource gates (hard reject on violation)
+
+- End-to-end wall clock ≤ 30 min on the selected AgentHLE gpu-free VM (1× NVIDIA L4).
+- Peak policy-side VRAM ≤ 8 GB (measured via
+  `torch.cuda.max_memory_allocated` delta around `Policy.inference`).
+- No subprocess spawns, no sockets opened from `policy.py`.
+
+## 8. Manual-review output (informational, not graded automatically)
+
+When `--video` is passed, one `videos/seed_<i>.mp4` per seed is
+produced for qualitative gait review. These are **not** used by the
+automated grader but archived alongside the score for human audit.

tasks/engineering/humanoid_velocity_tracking_policy/base/input/assets/__init__.py

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+"""Fixed articulation + URDF assets for the Humanoid Locomotion Challenge."""

tasks/engineering/humanoid_velocity_tracking_policy/base/input/assets/articulation_cfg.py

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+"""Articulation config for the Humanoid Locomotion Challenge robot.
+
+**DO NOT MODIFY** when submitting to the challenge — this file is part of
+the fixed evaluation surface.  Any change here will cause your
+submission to be evaluated against a different articulation than the one
+the baseline was trained against.
+
+URDF: ``assets/robot.urdf``.  All 23 joints are revolute — 12 legs
+(Hip_Pitch/Roll/Yaw, Knee_Pitch, Ankle_Pitch/Roll × 2) + 8 arms
+(Shoulder_Pitch/Roll, Elbow_Pitch/Yaw × 2) + Waist + 2 head (AAHead_yaw,
+Head_pitch).  The arm / waist / head joints are anchored near their
+tucked init pose by reward-side ``joint_deviation_l1`` terms at training
+time; at eval they are simply driven by the policy's action output.
+
+Leg PD: Hip/Knee stiffness 200 damping 5, Ankle stiffness 50 damping 1,
+armature 0.  Arm / waist / head PD: ``k = armature * (2π fn)²`` /
+``b = 2 ζ armature (2π fn)`` with ``fn = 10 Hz`` and ``ζ = 2``.
+"""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+import isaaclab.sim as sim_utils
+from isaaclab.actuators import ImplicitActuatorCfg
+from isaaclab.assets import ArticulationCfg
+
+
+# Resolve ``assets/robot.urdf`` relative to this file so the config works
+# regardless of the harness's current working directory.
+URDF_PATH: str = str((Path(__file__).resolve().parent / "robot.urdf"))
+
+
+# 23-DoF default pose.  Arms tucked to the sides via shoulder roll
+# ±1.3, slight forward shoulder pitch +0.2, elbow yaw ±0.5; waist and
+# head neutral; legs in a nominal crouch with Ankle_Pitch −0.25 rad.
+_DEFAULT_JOINT_POS: dict[str, float] = {
+    # Arms tucked.
+    "Left_Shoulder_Pitch": 0.20,
+    "Right_Shoulder_Pitch": 0.20,
+    "Left_Shoulder_Roll": -1.30,
+    "Right_Shoulder_Roll": 1.30,
+    "Left_Elbow_Pitch": 0.0,
+    "Right_Elbow_Pitch": 0.0,
+    "Left_Elbow_Yaw": -0.50,
+    "Right_Elbow_Yaw": 0.50,
+    # Waist + head neutral.
+    "Waist": 0.0,
+    "AAHead_yaw": 0.0,
+    "Head_pitch": 0.0,
+    # Legs: nominal stance.
+    "Left_Hip_Pitch": -0.20,
+    "Right_Hip_Pitch": -0.20,
+    "Left_Hip_Roll": 0.0,
+    "Right_Hip_Roll": 0.0,
+    "Left_Hip_Yaw": 0.0,
+    "Right_Hip_Yaw": 0.0,
+    "Left_Knee_Pitch": 0.40,
+    "Right_Knee_Pitch": 0.40,
+    "Left_Ankle_Pitch": -0.25,
+    "Right_Ankle_Pitch": -0.25,
+    "Left_Ankle_Roll": 0.0,
+    "Right_Ankle_Roll": 0.0,
+}
+
+
+# ---------------------------------------------------------------------------
+# Leg PD schedule.
+# ---------------------------------------------------------------------------
+_LEG_HIP_KNEE_K: float = 200.0
+_LEG_HIP_KNEE_B: float = 5.0
+_LEG_HIP_KNEE_EFFORT: float = 200.0
+_LEG_HIP_KNEE_VEL: float = 20.0
+
+_LEG_ANKLE_K: float = 50.0
+_LEG_ANKLE_B: float = 1.0
+_LEG_ANKLE_EFFORT: float = 100.0
+_LEG_ANKLE_VEL: float = 20.0
+
+
+# ---------------------------------------------------------------------------
+# Stiff PD for arms / waist / head.  Derivation:
+#   k = armature · (2π fn)² , b = 2 ζ armature (2π fn)   with fn=10 Hz, ζ=2.
+# ---------------------------------------------------------------------------
+_NATURAL_FREQ_HZ: float = 10.0
+_DAMPING_RATIO: float = 2.0
+_TWO_PI_FN: float = 2.0 * 3.1415926535 * _NATURAL_FREQ_HZ
+_STIFFNESS_COEFF: float = _TWO_PI_FN * _TWO_PI_FN           # ≈ 3947.84
+_DAMPING_COEFF: float = 2.0 * _DAMPING_RATIO * _TWO_PI_FN   # ≈ 251.33
+
+
+def _gains(armature: float) -> tuple[float, float]:
+    return armature * _STIFFNESS_COEFF, armature * _DAMPING_COEFF
+
+
+# Per-motor specs.
+_ARM_ARMATURE, _ARM_EFFORT, _ARM_VEL = 0.0282528, 38.3, 17.59
+_WAIST_ARMATURE, _WAIST_EFFORT, _WAIST_VEL = 0.0478125, 68.0, 14.66
+_HEAD_ARMATURE, _HEAD_EFFORT, _HEAD_VEL = 0.0018, 7.0, 12.57
+
+_ARM_K, _ARM_B = _gains(_ARM_ARMATURE)
+_WAIST_K, _WAIST_B = _gains(_WAIST_ARMATURE)
+_HEAD_K, _HEAD_B = _gains(_HEAD_ARMATURE)
+
+
+HUMANOID_CFG = ArticulationCfg(
+    spawn=sim_utils.UrdfFileCfg(
+        asset_path=URDF_PATH,
+        fix_base=False,
+        merge_fixed_joints=True,
+        make_instanceable=True,
+        activate_contact_sensors=True,
+        replace_cylinders_with_capsules=False,
+        joint_drive=sim_utils.UrdfConverterCfg.JointDriveCfg(
+            target_type="position",
+            gains=sim_utils.UrdfConverterCfg.JointDriveCfg.PDGainsCfg(
+                stiffness=0.0,
+                damping=0.0,
+            ),
+        ),
+        rigid_props=sim_utils.RigidBodyPropertiesCfg(
+            disable_gravity=False,
+            retain_accelerations=False,
+            linear_damping=0.0,
+            angular_damping=0.0,
+            max_linear_velocity=1000.0,
+            max_angular_velocity=1000.0,
+            max_depenetration_velocity=1.0,
+        ),
+        articulation_props=sim_utils.ArticulationRootPropertiesCfg(
+            enabled_self_collisions=True,
+            solver_position_iteration_count=8,
+            solver_velocity_iteration_count=4,
+        ),
+    ),
+    init_state=ArticulationCfg.InitialStateCfg(
+        pos=(0.0, 0.0, 0.72),
+        joint_pos=_DEFAULT_JOINT_POS,
+        joint_vel={".*": 0.0},
+    ),
+    soft_joint_pos_limit_factor=0.9,
+    actuators={
+        # Legs.
+        "hip_knee": ImplicitActuatorCfg(
+            joint_names_expr=[".*_Hip_Pitch", ".*_Hip_Roll", ".*_Hip_Yaw", ".*_Knee_Pitch"],
+            effort_limit_sim=_LEG_HIP_KNEE_EFFORT,
+            velocity_limit_sim=_LEG_HIP_KNEE_VEL,
+            stiffness=_LEG_HIP_KNEE_K,
+            damping=_LEG_HIP_KNEE_B,
+            armature=0.0,
+        ),
+        "ankle": ImplicitActuatorCfg(
+            joint_names_expr=[".*_Ankle_Pitch", ".*_Ankle_Roll"],
+            effort_limit_sim=_LEG_ANKLE_EFFORT,
+            velocity_limit_sim=_LEG_ANKLE_VEL,
+            stiffness=_LEG_ANKLE_K,
+            damping=_LEG_ANKLE_B,
+            armature=0.0,
+        ),
+        # Arms / waist / head — stiff PD.
+        "arms": ImplicitActuatorCfg(
+            joint_names_expr=[
+                ".*_Shoulder_Pitch",
+                ".*_Shoulder_Roll",
+                ".*_Elbow_Pitch",
+                ".*_Elbow_Yaw",
+            ],
+            effort_limit_sim=_ARM_EFFORT,
+            velocity_limit_sim=_ARM_VEL,
+            stiffness=_ARM_K,
+            damping=_ARM_B,
+            armature=_ARM_ARMATURE,
+        ),
+        "waist": ImplicitActuatorCfg(
+            joint_names_expr=["Waist"],
+            effort_limit_sim=_WAIST_EFFORT,
+            velocity_limit_sim=_WAIST_VEL,
+            stiffness=_WAIST_K,
+            damping=_WAIST_B,
+            armature=_WAIST_ARMATURE,
+        ),
+        "head": ImplicitActuatorCfg(
+            joint_names_expr=["AAHead_yaw", "Head_pitch"],
+            effort_limit_sim=_HEAD_EFFORT,
+            velocity_limit_sim=_HEAD_VEL,
+            stiffness=_HEAD_K,
+            damping=_HEAD_B,
+            armature=_HEAD_ARMATURE,
+        ),
+    },
+)
+"""Fixed humanoid articulation used by the challenge eval harness."""

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