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RooibosT/gr00t-n1.7-g1-dex1-ikea-relarm-30hz-h40-v2-bctinit

sourceHugging Faceapache-2.0updated 1mo agoView on Hugging Face
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IKEA v2 — BCT warm-start

GR00T N1.7 fine-tuned on carroll511/IKEA_table_assembly (v2 conversion) — a Unitree G1 with Dex1 grippers assembling a children's table from a fixed standing position.

g1_dex1_ikea_relarm_3view_aug_b64_v2_bctinit / checkpoint-20000.

Trades arm precision for gripper accuracy: gripper -9.6%, arm +1.2%, EE8 +2.2% against the baseline, same sign in all three tasks. Pick this one only if grasp retention fails before arm precision does.

Setup

initRooibosT/gr00t-n1.7-g1-dex1-bct-relarm-aug-30hz-h40 (round-2 ckpt-15000)
modality configexamples/unitree_g1_dex1_ikea/g1_dex1_ikea_relarm_3view_aug_config.py
state46 — identical key order to the BCT checkpoint, so the state encoder lines up
action16 dims — left_arm(7, RELATIVE), right_arm(7, RELATIVE), left_gripper, right_gripper
horizon40 @ 30 Hz
camerascam_left_high, cam_left_wrist, cam_right_wrist
trainingeffective batch 64 (global 16 x accum 4), 20,000 steps, 2x A100 DDP
backbonefrozen (tune_llm=False, tune_visual=False)

Open-loop accuracy

Scored on the held-out _v2_val split (26 episodes split at session boundaries, 697 windows at stride 10, 4 denoising steps, fixed per-window seed).

metriccheckpoint-20000mean of 16k/18k/20k
arm MAE, steps 1-8 (deg)1.4551.457
arm MAE, all 40 steps (deg)3.3403.338
wrist position error, steps 1-8 (mm)12.1012.11
wrist position error, all 40 (mm)20.9620.98
gripper MAE0.20830.2104

Per task:

tasknarm (deg)EE8 (mm)gripper
insert table leg to table base1822.83713.580.1568
pick table leg1802.8629.360.1975
rotate leg to tighten3353.87012.770.2420

Read the 1-8 step figures: async deployment executes about 8 steps after latency compensation and spends the rest of the chunk on RTC overlap, so steps past ~16 never run. eval_loss does not track action quality here and must not be used to pick a checkpoint.

These numbers come from the v2 val split and are not comparable to the earlier ...-30hz-h40 model's, which was scored on a different split.

Caveats

  • —Open-loop only. Closed-loop behaviour on hardware is unverified.
  • —The action space is RELATIVE for the arms and ABSOLUTE for the grippers; get_action() returns unnormalized absolute values.
  • —The waist is not commanded (the recordings are all from a fixed stance) and there is no locomotion signal in this dataset.