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Sim2Sim-OnePass Public Release

This curated layer is the fast path through the repository. It is designed so a new visitor can understand the claim, watch the evidence, inspect the canonical PASS artifacts, and run the shortest validation path without digging through the full development history.

Pick Your Route

If you want to... Open this
See the project in one screen RESULTS_SUMMARY.md
Watch the visual evidence first VISUAL_INDEX.md
Run the shortest validation path QUICKSTART.md
Inspect the packaged PASS bundle outputs/canonical_pass/
Understand how the repo is organized REPO_MAP.md

See It Before You Read It

Triptych preview Rollout figure
Triptych preview Rollout figure

Open the full visual package here:

The Claim In Plain Terms

After enforcing deterministic cross-simulator alignment between PyBullet and MuJoCo, this repo learns a residual next-state correction that:

  • reduces Bullet-to-MuJoCo one-step physical error,
  • remains stable under long-horizon rollout checks,
  • passes holdout and alignment gates,
  • and can be inspected visually through replay videos, triptychs, and overlay plots.

Canonical Story

  1. Deterministic paired plans are executed in PyBullet and MuJoCo.
  2. A strict alignment gate blocks training if reset state, timing, or first-step consistency drift.
  3. A residual model predicts the MuJoCo-minus-Bullet next-state gap.
  4. Hard-mode stress evaluation verifies one-step accuracy, holdouts, and rollout stability.
  5. Behavioral acceptance exports replay videos, triptychs, and overlay plots for inspection.

Canonical Evidence

  • Quantitative anchor: packaged in outputs/canonical_pass/source_stress_report.md and outputs/canonical_pass/source_stress_metrics.json
  • Visual anchor: packaged in outputs/canonical_pass/source_behavioral_report.md and the copied videos and preview images
  • Public-facing copied bundle: outputs/canonical_pass/
  • Provenance map: configs/canonical_sources.json

Exact Quickstart

This public repo is optimized for inspection first. Open QUICKSTART.md for the shortest path through the packaged evidence and for command references preserved from the source workspace.

What Lives Where

About

One-pass sim-to-sim alignment for robotics. Deterministic pairing, residual correction, and hard validation gates ensure stable, long-horizon behavior across simulators.

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