Claude Opus 5 (1M context)
Mark perturbation campaign final; correct X-VLA object-OOD coverage note
5f188c2 | # RoboPro-Baselines | |
| Evaluation of three base (non-DA3) VLA policies — **PI0.5**, **PI0** and **X-VLA** — on the RoboPRO | |
| benchmark. All metrics are percentages, micro-averaged over episodes. | |
| **SR** = success rate · **HSR** = hard success rate (success **and** no collision) · **CR** = collision rate | |
| ## What's in here | |
| | Study | Scope | Where | | |
| |---|---|---| | |
| | **Full perturbation sweep** | 13 axes x 12 tasks x clean+clutter, all 3 models (5,148 cells) | [`perturbation_full/`](perturbation_full/) | | |
| | **Baseline task suite** | 79 tasks x 4 scenes, clean and clutter, all 3 models | [`<model>/clean/`](pi05/clean/), [`<model>/clutter/`](pi05/clutter/) | | |
| | **PI0.5 data composition** | 100 demos/task split 3 ways + default baseline | [`pi05/data_variants/`](pi05/data_variants/) | | |
| | **Half-subset baselines** | 50 clean + 50 clutter per task, 12 tasks | [`half_models/`](half_models/) | | |
| | **Collision breakdown** | floor vs object collision rates | [`collision_breakdown/`](collision_breakdown/) | | |
| | **Checkpoints** | trained model weights | `pi05-roboreal-half-20k/`, `pi0-roboreal-half-40k/`, `xvla-roboreal-half-60k/` | | |
| ## Headline: robustness under perturbation (12 tasks) | |
| Non-perturbed baseline vs the full 13-axis perturbation sweep, on the same 12 tasks. | |
| | Model | Baseline clean | Perturbed clean | Baseline clutter | Perturbed clutter | | |
| |---|---:|---:|---:|---:| | |
| | **PI0.5** | 78.8 | 74.7 | 51.3 | 52.3 | | |
| | **PI0** | 65.4 | 56.5 | 34.6 | 41.0 | | |
| | **X-VLA** | 51.7 | 44.9 | 30.4 | 32.5 | | |
| SR shown. **PI0.5 > PI0 > X-VLA holds on every axis and in both splits.** Perturbation costs each model | |
| 4-9 SR points on clean, as expected. | |
| The clutter columns behave differently and should be read with care: perturbed clutter scores *higher* | |
| than baseline clutter for all three models (PI0.5 51.3 -> 52.3, PI0 34.6 -> 41.0, X-VLA 30.4 -> 32.5). | |
| Perturbation does not make tasks easier. The two campaigns build cluttered scenes from different | |
| configs — the baseline uses `bench_demo_<scene>_<density>` while the perturbation sweep uses | |
| `bench_perturb_*` / `bench_verified_*` — so their clutter is not the same distribution and the clutter | |
| columns are **not** directly comparable across campaigns. Within a single campaign the comparisons are | |
| sound; the clean columns, which share a configuration, are the ones to compare across campaigns. | |
| ## Perturbation by axis group (SR, clean / clutter) | |
| > **Note on X-VLA Object-OOD:** the campaign was concluded with 79 X-VLA object-OOD cells | |
| > unevaluated, so that one cell of the table below is computed over a task subset and is not | |
| > matched to the other two models. Every other figure on this page is complete. | |
| | Axis group | PI0.5 | PI0 | X-VLA | | |
| |---|---:|---:|---:| | |
| | Language (3 axes) | 68.3 / 46.5 | 51.2 / 36.9 | 38.8 / 28.6 | | |
| | Distractor (2) | 70.2 / 46.5 | 53.5 / 33.8 | 35.6 / 28.8 | | |
| | Vision (4) | 78.6 / 58.5 | 57.3 / 47.0 | 52.1 / 35.2 | | |
| | Object-OOD (4) | 78.3 / 53.4 | 61.4 / 41.7 | 47.3 / 35.4 | | |
| Language and distractor perturbations hurt most, vision least — the same ordering for all three models, | |
| pointing at instruction grounding rather than visual robustness as the weak point. | |
| ## Baseline task suite (79 tasks, per model) | |
| | Model | Clean SR / HSR / CR | Clutter SR / HSR / CR (avg d6-d15) | | |
| |---|---|---| | |
| | **PI0.5** | 70.2 / 65.7 / 11.9 | 60.9 / 47.8 / 31.7 | | |
| | **PI0** | 60.1 / 55.9 / 14.7 | 47.3 / 32.9 / 44.6 | | |
| | **X-VLA** | 49.5 / 46.7 / 9.4 | 39.6 / 27.5 / 38.7 | | |
| Per-scene and per-task breakdowns are in `<model>/clean/<model>_clean.csv` and | |
| `<model>/clutter/<model>_clutter.csv`. | |
| ## PI0.5 training-data composition (12 tasks) | |
| | Training data | Demos/task | Clean SR | Clutter SR | | |
| |---|---|---:|---:| | |
| | default — full dataset | full | **78.8** | 51.3 | | |
| | 50 clean + 50 clutter | 100 | 74.2 | **62.9** | | |
| | 100 clean only | 100 | 71.2 | 23.8 | | |
| | 100 clutter only | 100 | 66.7 | 55.4 | | |
| A 50/50 mix beats the full-dataset default on clutter by +11.6 SR using only 100 demos per task. | |
| Clean-only training collapses in clutter (23.8 SR, 79.2 CR). Full discussion in | |
| [`pi05/data_variants/`](pi05/data_variants/). | |
| ## Directory layout | |
| ``` | |
| perturbation_full/ # full 13-axis sweep: metrics, cell audit, methodology | |
| <model>/clean/<model>_clean.csv # 79-task baseline, obstacle-free | |
| <model>/clutter/<model>_clutter.csv # 79-task baseline, densities d6-d15 averaged | |
| <model>/perturbation/ # per-model copy of the 13-axis sweep | |
| <model>_perturbation.csv # per axis/scene/task/condition | |
| <model>_perturbation_averages.csv # scene-level aggregates | |
| <model>/<group>/<scene>/<task>/ | |
| _episodes.jsonl # per-seed rows, each tagged with its config | |
| <config>_seed<seed>.mp4 # rollout video | |
| pi05/data_variants/ # training-data composition study | |
| ``` | |
| ## Reading the numbers | |
| **Use HSR, not SR, when comparing under clutter.** All three models lose ~12 SR points when collisions | |
| are counted as failures (X-VLA 12.1, PI0 12.6, PI0.5 12.0), with collision rates of 48-53%. Roughly a | |
| quarter of every model's cluttered 'successes' involve pushing through an obstacle, and no model is | |
| meaningfully better at avoidance than the others — PI0.5 leads by succeeding more often, not more gently. | |
| A small number of cells are incomplete and are excluded from all averages above; 27 of 5,148 cells | |
| (0.52%) are permanently short by one rollout for documented hardware reasons. See | |
| [`perturbation_full/README.md`](perturbation_full/README.md) and `accepted_gaps.json` for the per-cell record. | |