fix: auto-adapt LeRobot state dimension instead of raising ValueError

[cagataycali]

TL;DR

When a robot exposes more joints than the policy was trained on (e.g. aloha has 16 joints but ACT expects 14), the policy raised a hard ValueError during inference. This fix auto-adapts state dimensions — truncate excess or zero-pad if fewer — with debug logging.

What changed

File	Change
strands_robots/policies/lerobot_local/policy.py	Replace ValueError with truncate/zero-pad + debug logging
tests/test_lerobot_local.py	Update test to assert pad behavior instead of raises

Why

This is the standard approach in robotics — LeRobot's own teleoperation code does the same. Hard crashing on dimension mismatch makes sim↔real transfer fragile and prevents running policies trained on one embodiment on another with different joint counts.

# Before: Hard crash
if len(state_values) != expected_dim:
    raise ValueError(f"State dimension mismatch: got {len(state_values)}...")

# After: Auto-adapt with logging
if len(state_values) > expected_dim:
    logger.debug("State dim %d > model expects %d — truncating", ...)
    state_values = state_values[:expected_dim]
elif len(state_values) < expected_dim:
    logger.debug("State dim %d < model expects %d — zero-padding", ...)
    state_values.extend([0.0] * (expected_dim - len(state_values)))

Testing

• ✅ All 266 existing tests pass
• ✅ Updated test_state_padded_to_expected_dim to verify auto-pad behavior
• ✅ Lint clean (ruff check + ruff format --check)

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Part 1 of 6 in the MuJoCo simulation PR decomposition (see PR_TASKS.md)

[yinsong1986]

The warning logs dimension counts but not key names. When a user sees State dim 16 > model expects 14 — truncating, they can't tell which joints are dropped. Consider adding key names to the message so users can verify the mapping is intentional vs. a genuine misconfiguration:

logger.warning(
    "State dim %d > model expects %d — truncating to first %d values. "
    "Check that robot_state_keys matches your robot's actual joint count.",
    len(state_values), expected_dim, expected_dim,
)

[cagataycali]

Fixed in 669735d — warning now includes actionable hint about robot_state_keys:

logger.warning(
    "State dim %d > model expects %d — truncating to first %d values. "
    "Check that robot_state_keys matches your robot's actual joint count.",
    len(state_values), expected_dim, expected_dim,
)

Same pattern applied to the zero-padding path.

[yinsong1986]

All review comments addressed. LGTM.