metadata
license: mit
task_categories:
- robotics
tags:
- lerobot
- mobile-manipulation
- vla
EBench: Elemental Mobile Manipulation Benchmark Dataset
Project Page | Paper | GitHub | Documentation
EBench is an indoor VLA (Vision-Language-Action) manipulation benchmark built on NVIDIA Isaac Sim. Instead of compressing a model's behavior into a single overall success rate, it produces a multi-axis capability profile that exposes what a model is good at — and where it overfits.
This repository contains the training trajectories (stored in the LeRobot format) used in the EBench evaluation suite.
Key Features
- Three manipulation regimes in one benchmark — covers long-horizon, dexterous & precise, and mobile manipulation.
- 5-axis atomic diagnostic — every task is labelled by Scene · Atomic Skill · Horizon · Precision · Mobility.
- 4-axis generalization tests — controlled perturbations along Object · Background · Instruction · Mixed.
- Strict train / test isolation — validation and unseen splits are open for tuning, while a held-out test split drives the leaderboard.
Citation
@misc{ebench2026,
title = {EBench: Elemental Mobile Manipulation Benchmark},
author = {Shanghai AI Laboratory},
year = {2026},
note = {Preprint coming soon},
url = {https://internrobotics.github.io/EBench-doc/}
}