| # `rskills/diffusion-pusht/eval/` — benchmark results | |
| `pusht.json` is the PushT mean-coverage-IoU benchmark result block for this | |
| rSkill. Validated against | |
| [`openral_core.RSkillEvalResult`](../../../docs/reference/schemas/RSkillEvalResult.json) | |
| at load time by the `rSkill` loader and surfaced by `openral benchmark report`. | |
| | Field | Value | | |
| | --- | --- | | |
| | Source | Chi et al., 2023 — *Diffusion Policy: Visuomotor Policy Learning via Action Diffusion* (arxiv:2303.04137) | | |
| | Benchmark | PushT (`gym_pusht/PushT-v0`, pymunk 2-D rigid-body) | | |
| | Robot | PushT 2-D pseudo-robot (single 2-D end-effector tip) | | |
| | Reproduced locally? | ✗ — paper-only. `tests/sim/test_pusht_2d_diffusion_pusht.py` runs a single episode for IO + latency + VRAM verification. | | |
| | Reproduce | `just sim-diffusion-pusht` (single episode); raise `--n-episodes 50` for the full paper protocol. | | |