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iros-experiments

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Use when designing or auditing IROS experiments — real-robot trial counts, success criteria set in advance, reset procedures, failure taxonomies, baseline fairness on matched hardware, sim-to-real gap reporting, small-n statistics, and the claim-to-evidence ladder that embodied-systems reviewers apply before they trust a demo.

IROS-Skills/skills/iros-experiments/SKILL.md

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# IROS Experiments

Use this before submission when the empirical story is not yet locked. At IROS, experiments exist to
prove a robot did something reliably, under stated conditions — not to top a leaderboard.

## Experiment audit

- Map each claim to the evidence that supports it: a real-robot trial set, a simulation study, an
  ablation, or a field deployment. A claim with no matched evidence is an overclaim.
- Define the **success criterion before running**, in one sentence a skeptic would accept, and hold to
  it; a criterion invented after seeing results is a reviewer red flag.
- Report **trial counts and resets**: how many attempts, how start conditions were randomized, and what
  reset happened between trials. Hidden resets inflate reliability.
- Publish a **failure taxonomy** with counts, not just a success rate; the failures are where reviewers
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