---
task_categories:
- robotics
tags:
- manipulation
- imitation-learning
- visuomotor-policies
- short-term-memory
---

# ReMemBench: Scaling Short-Term Memory of Visuomotor Policies for Long-Horizon Tasks

[**[Project Page]**](https://shahrutav.github.io/short-term-memory/)   [**[Paper]**](https://huggingface.co/papers/2606.16178)   [**[GitHub]**](https://github.com/ShahRutav/ReMemBench)

ReMemBench is a benchmark consisting of eight diverse household manipulation tasks spanning four categories of short-term memory, designed to foster general memory mechanisms in robotic visuomotor policies. Built upon [RoboCasa](https://robocasa.ai/), it provides expert teleoperated demonstrations for training and evaluating policies in long-horizon tasks.

## Task Categories

Tasks are organized by memory type. Each task is provided with 50 expert demonstrations for training.

| Task Name | Memory Category | Task Variants |
|-----------|----------------|---------------|
| **Retrieve Fruit**<br/>Remember fruit location (out of view). | **Spatial Memory**<br/>*Recall object locations* | `MemFruitInSinkLeftFar`<br/>`MemFruitInSinkRightFar` |
| **Retrieve Oil**<br/>Remember oil bottle location among distractors. | **Spatial Memory**<br/>*Recall object locations* | `MemRetrieveOilsFromCounterLL`<br/>`MemRetrieveOilsFromCounterLR`<br/>`MemRetrieveOilsFromCounterRL`<br/>`MemRetrieveOilsFromCounterRR` |
| **Cook Meat**<br/>Remember cooking duration while waiting. | **Prospective Memory**<br/>*Retain intentions over delay* | `MemHeatPot` |
| **Cook Meat and Vegetable**<br/>Remember multiple timed actions. | **Prospective Memory**<br/>*Retain intentions over delay* | `MemHeatPotMultiple` |
| **Wash and Return to Container**<br/>Remember which saucer (left/right) the fruit came from. | **Object-Associative Memory**<br/>*Recall associations* | `MemWashAndReturnLeft`<br/>`MemWashAndReturnRight` |
| **Wash and Return to Original Spot**<br/>Remember original countertop location. | **Object-Associative Memory**<br/>*Recall associations* | `MemWashAndReturnSameLocation` |
| **Microwave Breadsticks**<br/>Remember count of breadsticks moved. | **Object-Set Memory**<br/>*Maintain/update sets* | `MemPutKBreadInMicrowave` |
| **Relocate Bowls**<br/>Remember count of bowls among distractors. | **Object-Set Memory**<br/>*Maintain/update sets* | `MemPutKBowlInCabinet` |

## Data Downloading 

You can download the dataset using the `huggingface-cli`:

```bash
huggingface-cli download Rutav/ReMemBench-Dataset \
  --repo-type dataset \
  --local-dir ReMemBench-Dataset \
  --local-dir-use-symlinks False
```

## Dataset Structure

The dataset is organized by task name, with each task containing demonstration sessions in HDF5 format.

### File Structure
```
ReMemBench-Dataset/
├── MemFruitInSinkLeftFar/
├── MemHeatPot/
│   ├── [timestamp]/
│   │   ├── demo.hdf5
│   │   └── demo_im128.hdf5  # Image version
├── ...
└── task_embeds_clip_v3.pickle
```

### HDF5 File Structure (`demo_im128.hdf5`)
- **`actions`**: (T, 12) - [7D arm, 4D base, 1D mode]
- **`obs`**:
    - `robot0_joint_pos_cos` / `robot0_joint_pos_sin`: (T, 7) - Joint position encoding
    - `robot0_gripper_qpos`: (T, 2) - Gripper position
    - `robot0_agentview_center_image`: (T, 128, 128, 3) - RGB third-person view
    - `robot0_eye_in_hand_image`: (T, 128, 128, 3) - RGB eye-in-hand view
- **`rewards`**, **`dones`**, **`states`**: Standard simulation signals

## Exploring the Data

To visualize demonstrations, use the `replay_dataset.py` script from the [official repository](https://github.com/ShahRutav/ReMemBench):

```bash
python robocasa/scripts/replay_dataset.py \
  --hdf5_path ReMemBench-Dataset/MemHeatPot/[timestamp]/demo_im128.hdf5 \
  --episode_idx 0 \
  --render
```

## Converting to LeRobot Dataset Format

A conversion script is provided in the repository to port the data to [LeRobot](https://github.com/huggingface/lerobot) format:

```bash
python robocasa/scripts/port_to_lerobot.py \
  --dataset_path ReMemBench-Dataset/MemHeatPot/[timestamp]/demo_im128.hdf5 \
  --repo_name your_hf_username/MemHeatPot
```

## Citation

```bibtex
@article{shah2024scaling,
  title={Scaling Short-Term Memory of Visuomotor Policies for Long-Horizon Tasks},
  author={Shah, Rutav and others},
  journal={arXiv preprint arXiv:2606.16178},
  year={2024}
}
```