| --- |
| license: apache-2.0 |
| tags: |
| - robotics |
| - vision-language-action |
| - manipulation |
| --- |
| |
| # BridgeVLA++ |
|
|
| Pre-training data, checkpoints and benchmark keyframe data for **BridgeVLA++** and its |
| predecessor **BridgeVLA**. |
|
|
| BridgeVLA++ is a 3D vision-language-action framework that preserves the input-output |
| alignment of a pre-trained VLM during 3D action learning — point clouds are projected |
| into multi-view images and intermediate heatmaps are predicted before actions — and |
| extends it with a unified **spatio-temporal memory** modeling persistent spatial |
| context and temporal interaction history. It matches or surpasses BridgeVLA on the |
| original benchmarks without sacrificing data efficiency or generalization, reaches |
| state of the art on two memory-dependent benchmarks, and extends to bimanual |
| manipulation and a new real-world embodiment. |
|
|
| ## Contents |
|
|
| ``` |
| checkpoints/ |
| ├── pretrain/ # grounding pre-training weights, shared by both models (finetune warm-start) |
| ├── bridgevla/ # BridgeVLA (original) |
| │ └── rlbench/ colosseum/ gembench/ |
| └── bridgevla_plus/ # BridgeVLA++ weights |
| ├── rlbench/ colosseum/ gembench/ memorybench/ |
| └── rmbench/<task>/ # per-task, 9 tasks |
| pretrain_data/ |
| ├── coco.tar.gz # COCO images |
| └── detection_data.json # RoboPoint grounding annotations |
| datasets/ # benchmark keyframe data (see below) |
| ├── rlbench/keyframe_cache/size128_v2/<task>/episode<N>.npz + .npz.meta |
| ├── memorybench/keyframe_cache/size128_v3/<task>/episode<N>.npz + .npz.meta |
| └── rmbench/ |
| ├── keyframe_data/<task>/keyframe_depth/ # keyframe-only HDF5 training data |
| └── keyframes/<task>.json # keyframe metadata -> memory labels |
| ``` |
|
|
| ### Benchmark keyframe data |
|
|
| `datasets/` ships the precomputed keyframe artifacts training depends on — do not |
| rearrange them by hand; the code repo's `scripts/download_checkpoints_hf.sh` (or |
| `scripts/download_checkpoints_ms.sh` for the identical ModelScope mirror) with a |
| target of `rlbench_cache` / `memorybench_cache` / `rmbench_data` (or per-task |
| `rmbench_data:<task>`) places each into the exact layout the trainers expect: |
|
|
| - **rlbench / memorybench `keyframe_cache`** — pre-built episode caches |
| (`.npz` decoded observations + `.meta` canonical keyframe indices). The |
| `.meta` files pin RLBench's per-(task, variation) majority-vote canonical |
| keyframes: shipping them makes training runs reproduce ours exactly, and |
| skips a multi-hour local build. RLBench training *requires* this cache. |
| - **rmbench `keyframe_data` + `keyframes`** — the actual RMBench training set |
| (keyframe-only re-rendered HDF5, 50 episodes x 10 tasks) plus per-keyframe |
| metadata whose `language_annotation`/`subtask_idx` provide the memory |
| supervision labels. With these, the raw 37 GiB demo_clean demos are NOT |
| needed for training or evaluation. The two directories must stay siblings. |
| |
| If you download this repo manually instead (e.g. `huggingface-cli download` / |
| `modelscope download` of the whole repo), place each tree as below. The local |
| names differ from the repo paths **on purpose** (`_keyframe_cache` has a leading |
| underscore; capitalization and nesting differ too), so copying `datasets/` into |
| the code repo as-is will NOT be found by the trainers: |
| |
| | in this repo | local path in the code repo | |
| |---|---| |
| | `checkpoints/` | `data/bridgevla_ckpt/` (inner layout unchanged) | |
| | `pretrain_data/` | `data/bridgevla_data/pretrain_data/` | |
| | `datasets/rlbench/keyframe_cache/` | `data/bridgevla_data/RLBench/_keyframe_cache/` | |
| | `datasets/memorybench/keyframe_cache/` | `data/bridgevla_data/memorybench/data/train/_keyframe_cache/` | |
| | `datasets/rmbench/keyframe_data/` | `data/bridgevla_data/RMBench/data/keyframe_data/` | |
| | `datasets/rmbench/keyframes/` | `data/bridgevla_data/RMBench/data/keyframes/` | |
|
|
| A misplaced path never degrades silently: training fails fast with an error |
| naming the expected location and the download command that fills it. |
|
|
| Every checkpoint directory holds `model_<epoch>.pth` together with `exp_cfg.yaml` and |
| `mvt_cfg.yaml`; the two configs define the network architecture and must stay next to |
| the weights. |
|
|
| | epoch | RLBench | COLOSSEUM | GemBench | memoryBench | RMBench | |
| |---|---|---|---|---|---| |
| | BridgeVLA++ | 130 | 200 | 200 | 160 | per-task | |
| | BridgeVLA | 80 | 80 | 40 | – | – | |
|
|
| The `bridgevla/` checkpoints belong to the original BridgeVLA codebase and are **not** |
| loadable by BridgeVLA++; run them with that codebase. Only `pretrain/` is shared by both. |
|
|
| ## Papers |
|
|
| - **BridgeVLA++: A Data-Efficient, Generalizable, and Memory-Augmented Vision-Language-Action Framework for 3D Manipulation** — arXiv coming soon. |
| - **BridgeVLA: Input-Output Alignment for Efficient 3D Manipulation Learning with Vision-Language Models** — [arXiv:2506.07961](https://arxiv.org/abs/2506.07961) |
|
|
| Usage instructions live in the code repository. |
|
|
| ## Provenance |
|
|
| `pretrain/`, `bridgevla/` and `pretrain_data/` are the artifacts released with |
| BridgeVLA. `pretrain_data/` builds on COCO images and RoboPoint-style grounding |
| annotations, which remain subject to their original terms; the Apache-2.0 license above |
| applies to the model weights. |
|
|
| `datasets/` is derived data: the rlbench cache from the PerAct RLBench demos |
| (hqfang/rlbench-18-tasks), the memorybench cache from SAM2Act's MemoryBench data |
| (hqfang/memorybench), and the rmbench trees re-rendered from RoboTwin 2.0 / RMBench |
| (TianxingChen/RMBench). Each remains subject to its upstream benchmark's terms. |
|
|
