UCBProject/baseline_3_v4_collection_assets

baseline_3 v4 — sim collection assets

2026-05-26 — STATUS: ARCHIVED / REFERENCE-ONLY.

The plan to run sim collection on the A6000 was abandoned this round due to a glibc incompatibility: the A6000 system glibc is 2.31 (Ubuntu 20.04) but IsaacSim 5.1.0 requires glibc 2.35 (Ubuntu 24.04). All sim collection (DexYCB + OakInk) was completed on the dev box (RTX 5090).

The contents of this dataset (tarballs of source episodes, USDs, scripts, partial results log) are kept for reference and reproducibility — the code links remain accurate — but the "run the resume on A6000" instructions below are no longer the current plan.

For the current state of the data and training pipeline, see:

• DexYCB-sourced training trajectories (162 ep) → UCBProject/DP3_DexYCB_training_data
• OakInk-sourced training trajectories (207 ep) → UCBProject/DP3_OakInk_training_data

The DexYCB README also documents the new combined 369-ep training run on A6000.

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What's in this archived package

file	size	purpose
episodes_g.tar.gz	1.2 GB	900 retargeted DexYCB hdf5 (collector INPUT for the sim collection that ran on the dev box). Includes ycb_dex_01–20 minus the no-data ones; specifically the newly retargeted dex_11 (pitcher) + dex_14 (mug) missing from previous runs.
obj_usd_cad_ycb.tar.gz	489 MB	YCB CAD USDs (17 files, Z-up tagged) + textures. Includes the new dex_11/14/19 USDs generated this round.
episodes_b3_v4_15obj_3yaw_2026-05-25.tar.gz	266 MB	Already-collected sim hdf5 for 6 objects (tuna 06, tomato 04, pudding 07, gelatin 08, marker 18, potted_meat 09) at the time the partial results log was snapshotted.
v4_full15_results_2026-05-25.txt	1.5 KB	Partial results log with 6 DONE_RETRY entries (point-in-time snapshot before the run continued on the dev box).
v4_full15_queue_resume.sh	4.6 KB	Resume-aware orchestrator (2-parallel). Repo canonical version under scripts/baseline_3_v4/.
v4_chunked_with_retry.sh	4.6 KB	Per-object chunk-5+retry wrapper. Repo canonical version under scripts/baseline_3_v4/.

Source code (canonical): stzabl-png/UCB_Project @ gate3-curobo-ik — sim/run_grasp_sim_baseline3_v4.py and scripts/baseline_3_v4/*.sh.

The OakInk-specific orchestrator (added 2026-05-26) lives at scripts/baseline_3_v4/oakink_full89_queue_resume.sh in the same repo.

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How sim collection actually ran (2026-05-25 + 2026-05-26)

All on the dev box (RTX 5090, Ubuntu 24.04, glibc 2.35):

Run	Date	Result
DexYCB resume — 15 obj, 2-parallel chunked-5	2026-05-25	162 successful trajectories across 10 objects → UCBProject/DP3_DexYCB_training_data
OakInk full — 89 obj, 2-parallel chunked-5	2026-05-26	207 successful trajectories across 45 objects (44 obj contributed 0 due to obj geometry / Franka kinematic limits) → UCBProject/DP3_OakInk_training_data

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Why the A6000 was dropped from the collection pipeline

Diagnosed 2026-05-25:

$ python -c "from isaacsim import SimulationApp"
ImportError: /lib/x86_64-linux-gnu/libc.so.6: version 'GLIBC_2.35' not found
(required by .../isaacsim-5.1.0/_build/lib/libomni.kit.app.so)

A6000 system glibc 2.31 is fixed by the Ubuntu 20.04 base; bumping the system libc to 2.35 in-place is not safe. Containerizing IsaacSim would work but adds a deployment burden we decided wasn't worth it for sim collection that runs on the dev box anyway. The A6000 stays on training.

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Original "resume on A6000" instructions (DEPRECATED — kept for reference)

Click to expand the original A6000 sim-collection guide. This was written before the glibc issue was diagnosed; it is no longer the plan. Follow the new training instructions in the DexYCB dataset README instead.

The instructions below describe how the A6000 sim collection would have worked if glibc had been compatible. They are kept verbatim for reproducibility; do not follow them on the current A6000.

env_isaaclab install (requires glibc ≥ 2.35)

conda create -n env_isaaclab python=3.11 -y
conda activate env_isaaclab
pip install --upgrade --extra-index-url=https://pypi.nvidia.com isaacsim==5.1.0
pip install --extra-index-url=https://pypi.nvidia.com nvidia-curobo
pip install h5py scipy 'numpy<2' termcolor pyyaml requests usd-core

Download + extract from this archive

cd UCB_Project
pip install huggingface_hub
mkdir -p Baseline1/data output
huggingface-cli download UCBProject/baseline_3_v4_collection_assets \
    --repo-type dataset --local-dir /tmp/v4_pkg
tar xzf /tmp/v4_pkg/episodes_g.tar.gz
tar xzf /tmp/v4_pkg/obj_usd_cad_ycb.tar.gz
tar xzf /tmp/v4_pkg/episodes_b3_v4_15obj_3yaw_2026-05-25.tar.gz
cp /tmp/v4_pkg/v4_full15_results_2026-05-25.txt /tmp/

Run the resume

cd UCB_Project
PROJ=$HOME/UCB_Project \
PY=$HOME/miniconda3/envs/env_isaaclab/bin/python \
OUT=Baseline1/data/episodes_b3_v4_15obj_3yaw_2026-05-25 \
RESULTS=/tmp/v4_full15_results_2026-05-25.txt \
PAR=2 \
  bash scripts/baseline_3_v4/v4_full15_queue_resume.sh

For PAR tuning, gotcha list, troubleshooting, and per-object expected yield, see the original 10-gotcha table that previously appeared here — the canonical version is now in the repo's Baseline1/RETRAIN_V4_FULL12.md and the inline comments in scripts/baseline_3_v4/v4_*.sh.

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License & citation

Sim collection assets: CC-BY-4.0. DexYCB source data subject to the original DexYCB license. YCB object meshes: Yale-CMU-Berkeley YCB Object & Model Set license.