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1. Repository Layout

Key directories:

  • src/robot_memory_vla/
    • main project source code
  • configs/
    • project configuration
  • scripts/
    • setup and asset download scripts
  • external/graspnet/
    • repository-local graspnet code and checkpoint location

2. Installation

cd <repo-root>
bash scripts/bootstrap.sh

If you prefer manual setup:

cd <repo-root>
conda activate robotvla39  # if you use conda
python -m pip install -e '.[dev]'

3. Download Assets

To download or localize model assets:

cd <repo-root>
export GENERALVLA_PRETRAIN_SOURCE=/path/to/existing/pretrain_model  # optional
bash scripts/download_assets.sh

The script populates repository-local paths such as:

  • vendor/GeneralVLA/pretrain_model/LISA-7B-v1-explanatory
  • vendor/GeneralVLA/pretrain_model/segagent/zzzmmz/SegAgent-Model
  • vendor/GeneralVLA/pretrain_model/sam_vit_h_4b8939.pth
  • vendor/GeneralVLA/pretrain_model/clip-vit-large-patch14

Notes:

  • these files are large and require enough disk space
  • if disk space is insufficient, the script will fail and preflight will continue reporting missing assets

4. Configuration

Configuration files are located in:

  • configs/models.yaml
  • configs/robot.yaml
  • configs/runtime.yaml

The shipped defaults now use repository-relative paths.

configs/models.yaml

Controls:

  • vendored source directories
  • GeneralVLA model locations
  • GraspNet paths
  • inference parameters

configs/robot.yaml

Controls:

  • real robot TCP endpoint
  • gripper defaults
  • robot initial pose

configs/runtime.yaml

Controls:

  • runtime output directories
  • memory file path
  • retrieval top_k
  • whether execution requires operator confirmation

5. Verification

5.1 Run Tests

cd <repo-root>
conda activate robotvla39  # if you use conda
pytest -q

Current verified result:

33 passed

5.2 Preflight Check

cd <repo-root>
conda activate robotvla39  # if you use conda
python -m robot_memory_vla.app.main --preflight --config-dir ./configs

Behavior:

  • if the repository-local assets are present, preflight should pass
  • if the assets are missing, preflight will report the missing repo-local model paths

6. Run the Main Flow

cd <repo-root>
conda activate robotvla39  # if you use conda
python -m robot_memory_vla.app.main \
  --config-dir ./configs \
  --task "Pick up the bottle cap on the desk and place it on the pink box in the lower-right corner"

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GeneralVLA: Generalizable Vision-Language-Action Models with Knowledge-Guided Trajectory Planning

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