| | --- |
| | annotations_creators: |
| | - machine-generated |
| | language: |
| | - en |
| | language_creators: |
| | - machine-generated |
| | license: mit |
| | task_categories: |
| | - robotics |
| | - reinforcement-learning |
| | - video-to-video |
| | task_ids: |
| | - grasping |
| | - task-planning |
| | tags: |
| | - world-model |
| | - simulator |
| | - friction |
| | - contact-dynamics |
| | - physics-simulation |
| | - dynamics-prediction |
| | pretty_name: DreamerBench |
| | size_categories: |
| | - n<1K |
| | --- |
| | |
| | # Dataset Card for DreamerBench |
| |
|
| | ## Table of Contents |
| | - [Dataset Description](#dataset-description) |
| | - [Dataset Summary](#dataset-summary) |
| | - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
| | - [Languages](#languages) |
| | - [Dataset Structure](#dataset-structure) |
| | - [Data Instances](#data-instances) |
| | - [Data Fields](#data-fields) |
| | - [Data Splits](#data-splits) |
| | - [Dataset Creation](#dataset-creation) |
| | - [Curation Rationale](#curation-rationale) |
| | - [Source Data](#source-data) |
| | - [Personal and Sensitive Information](#personal-and-sensitive-information) |
| | - [Considerations for Using the Data](#considerations-for-using-the-data) |
| | - [Social Impact of Dataset](#social-impact-of-dataset) |
| | - [Discussion of Biases](#discussion-of-biases) |
| | - [Other Known Limitations](#other-known-limitations) |
| | - [Additional Information](#additional-information) |
| | - [Dataset Curators](#dataset-curators) |
| | - [Licensing Information](#licensing-information) |
| | - [Citation Information](#citation-information) |
| |
|
| | ## Dataset Description |
| |
|
| | - **Homepage:** [TODO: Link to project website or repository] |
| | - **Repository:** https://github.com/uwsbel/ChronoDreamer |
| | - **Paper:** [TODO: Link to arXiv paper if available] |
| | - **Point of Contact:** Json Zhou, zzhou292@wisc.edu |
| |
|
| | ### Dataset Summary |
| |
|
| | **DreamerBench** is a large-scale dataset designed for training and evaluating **World Models** in robotics applications. Unlike standard visual-only datasets, DreamerBench explicitly focuses on physical interaction dynamics, specifically **friction** and **contact data**. |
| |
|
| | The dataset is generated using Project Chrono (https://projectchrono.org/), simulating diverse robotic interaction scenarios where precise modeling of physical forces is critical. It includes pre-computed **encodings** to facilitate efficient training of latent dynamics models. |
| |
|
| | Key features: |
| | * **Physical Fidelity:** detailed ground-truth annotations for coefficient of friction, contact forces, and slip. |
| | * **Multi-Modal:** Contains visual observations (RGB/Depth), proprioceptive states, and explicit physics parameters. |
| | * **World Model Ready:** Structured to support next-step prediction and imaginary rollout training (Dreamer-style architectures). |
| |
|
| | ### Supported Tasks and Leaderboards |
| |
|
| | * **World Modeling / Dynamics Learning:** Training models to predict future states ($s_{t+1}$) given current state ($s_t$) and action ($a_t$). |
| | * **Offline Reinforcement Learning:** Learning policies from the provided simulator trajectories without active environmental interaction. |
| | * **Sim-to-Real Adaptation:** Using the varied friction/contact parameters to train robust policies that generalize to real-world physics. |
| | |
| | ## Dataset Structure |
| | |
| | ### Data Instances |
| | |
| | Each instance in the dataset represents a **trajectory** or **episode** of a robot interacting with the environment. |
| | |
| | **Example structure (JSON/Parquet format):** |
| | |
| | ```json |
| | { |
| | "episode_id": "traj_001", |
| | "steps": 1000, |
| | "observations": { |
| | "rgb": [Array of (1000, 64, 64, 3) images], |
| | "depth": [Array of (1000, 64, 64, 1) images], |
| | "proprioception": [Array of joint angles/velocities] |
| | }, |
| | "actions": [Array of control inputs], |
| | "rewards": [Array of float scalars], |
| | "physics_data": { |
| | "contact_forces": [Array of 3D force vectors], |
| | "friction_coefficient": 0.8, |
| | "contact_detected": [Binary array] |
| | }, |
| | "encoding": [Pre-computed latent vectors, e.g., VAE or RSSM states] |
| | } |
| | ``` |
| | |
| | **Example scenarios:** |
| | <h3>Visual Data Samples</h3> |
| | <p>Examples of 3 scenarios across 4 different camera angles (256x256).</p> |
| |
|
| | <table> |
| | <thead> |
| | <tr> |
| | <th style="text-align: center">Scenario</th> |
| | <th style="text-align: center">Ego</th> |
| | <th style="text-align: center">Side 1</th> |
| | <th style="text-align: center">Side 2</th> |
| | <th style="text-align: center">Contact Splat</th> |
| | </tr> |
| | </thead> |
| | <tbody> |
| | <tr> |
| | <td style="vertical-align: middle; font-weight: bold;">flashlight-box</td> |
| | <td> |
| | <video src="https://huggingface.co/datasets/YOUR_USERNAME/DreamerBench/resolve/main/videos/scen1_cam1.mp4" autoplay loop muted playsinline width="256px"></video> |
| | </td> |
| | <td> |
| | <video src="https://huggingface.co/datasets/YOUR_USERNAME/DreamerBench/resolve/main/videos/scen1_cam2.mp4" autoplay loop muted playsinline width="256px"></video> |
| | </td> |
| | <td> |
| | <video src="https://huggingface.co/datasets/YOUR_USERNAME/DreamerBench/resolve/main/videos/scen1_cam3.mp4" autoplay loop muted playsinline width="256px"></video> |
| | </td> |
| | <td> |
| | <video src="https://huggingface.co/datasets/YOUR_USERNAME/DreamerBench/resolve/main/videos/scen1_cam4.mp4" autoplay loop muted playsinline width="256px"></video> |
| | </td> |
| | </tr> |
| | <tr> |
| | <td style="vertical-align: middle; font-weight: bold;">flashlight-coca</td> |
| | <td> |
| | <video src="https://huggingface.co/datasets/YOUR_USERNAME/DreamerBench/resolve/main/videos/scen2_cam1.mp4" autoplay loop muted playsinline width="256px"></video> |
| | </td> |
| | <td> |
| | <video src="https://huggingface.co/datasets/YOUR_USERNAME/DreamerBench/resolve/main/videos/scen2_cam2.mp4" autoplay loop muted playsinline width="256px"></video> |
| | </td> |
| | <td> |
| | <video src="https://huggingface.co/datasets/YOUR_USERNAME/DreamerBench/resolve/main/videos/scen2_cam3.mp4" autoplay loop muted playsinline width="256px"></video> |
| | </td> |
| | <td> |
| | <video src="https://huggingface.co/datasets/YOUR_USERNAME/DreamerBench/resolve/main/videos/scen2_cam4.mp4" autoplay loop muted playsinline width="256px"></video> |
| | </td> |
| | </tr> |
| | <tr> |
| | <td style="vertical-align: middle; font-weight: bold;">waterbottle-coca</td> |
| | <td> |
| | <video src="https://huggingface.co/datasets/YOUR_USERNAME/DreamerBench/resolve/main/videos/scen3_cam1.mp4" autoplay loop muted playsinline width="256px"></video> |
| | </td> |
| | <td> |
| | <video src="https://huggingface.co/datasets/YOUR_USERNAME/DreamerBench/resolve/main/videos/scen3_cam2.mp4" autoplay loop muted playsinline width="256px"></video> |
| | </td> |
| | <td> |
| | <video src="https://huggingface.co/datasets/YOUR_USERNAME/DreamerBench/resolve/main/videos/scen3_cam3.mp4" autoplay loop muted playsinline width="256px"></video> |
| | </td> |
| | <td> |
| | <video src="https://huggingface.co/datasets/YOUR_USERNAME/DreamerBench/resolve/main/videos/scen3_cam4.mp4" autoplay loop muted playsinline width="256px"></video> |
| | </td> |
| | </tr> |
| | </tbody> |
| | </table> |
