Robotics
PEFT
Safetensors
navigation
objectnav
pointnav
vision-language-action
habitat
flow-matching
Instructions to use Aasdfip/longnav-objectnav-flow-nopose-cotrain-2p5hz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Aasdfip/longnav-objectnav-flow-nopose-cotrain-2p5hz with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Correct path-length label; add the 140 s (350-step) arm
Browse files
README.md
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@@ -163,7 +163,8 @@ paired on the same episodes.
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| oracle SPL (corrected, see below) | **0.348** |
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| NPWPL | **0.420** |
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| closest approach | 2.25 m |
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| path length | 14.26 m |
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Against the other checkpoints in this family, same episodes, same 70 s budget:
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does not reliably retrieve a goal announced once, deep in context. This model's PointNav
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component is there to teach a motion repertoire, not goal-following; do not deploy it as
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a point-goal navigator.
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* **
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* **0.56 epochs** over its mixture -- undertrained rather than converged.
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* Trained on MP3D human demonstrations, evaluated on HM3D -- cross-dataset.
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* n=101 has a minimum detectable difference of roughly 0.10 on a success rate. Differences
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| oracle SPL (corrected, see below) | **0.348** |
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| NPWPL | **0.420** |
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| closest approach | 2.25 m |
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| path length at closest approach | 14.26 m |
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| total path length | 19.83 m |
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Against the other checkpoints in this family, same episodes, same 70 s budget:
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does not reliably retrieve a goal announced once, deep in context. This model's PointNav
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component is there to teach a motion repertoire, not goal-following; do not deploy it as
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a point-goal navigator.
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* **The efficiency lead is a 70 s result; the oracle lead holds at 140 s.** Doubling the
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budget (`--max-steps 350`) raises oracle success to **0.733** -- still the best of the
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flow-head family, and ahead of the 1:1 sibling's 0.703 -- but corrected oSPL falls to
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**0.325** and NPWPL to 0.366, so the 1:1 sibling (0.339 / 0.384) matches it on
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efficiency there. Within this checkpoint the 175 -> 350 gain is not significant
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(McNemar p = 0.14; oSPL delta -0.024, 95% CI [-0.079, +0.031]). Read the 70 s numbers as
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the efficiency claim and the 140 s numbers as the reachability claim.
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* **0.56 epochs** over its mixture -- undertrained rather than converged.
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* Trained on MP3D human demonstrations, evaluated on HM3D -- cross-dataset.
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* n=101 has a minimum detectable difference of roughly 0.10 on a success rate. Differences
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