UniVTAC
收藏魔搭社区2026-05-17 更新2026-05-03 收录
下载链接:
https://modelscope.cn/datasets/byml2024/UniVTAC
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# UniVTAC Benchmark Dataset
The UniVTAC Benchmark dataset provides simulation data for tactile-based robotic manipulation tasks.
## Overview
This dataset contains 100 episodes per task, totaling 800 episodes across 8 diverse manipulation tasks.
## Task Gallery
UniVTAC Benchmark currently includes the following manipulation tasks, all featuring tactile sensing:
| Task | Module | Description |
|---|---|---|
| **Collect** | `collect` | Collect contact-rich tactile data for pretraining |
| **Lift Bottle** | `lift_bottle` | Grasp and lift a bottle off a surface near a wall |
| **Lift Can** | `lift_can` | Grasp and lift a cylindrical can |
| **Insert HDMI** | `insert_HDMI` | Insert an HDMI connector into a port |
| **Insert Hole** | `insert_hole` | Precision peg-in-hole insertion |
| **Insert Tube** | `insert_tube` | Insert a tube into a fixture |
| **Pull Out Key** | `pull_out_key` | Extract a key from a lock |
| **Put Bottle in Shelf** | `put_bottle_in_shelf` | Place a bottle onto a shelf |
| **Grasp & Classify** | `grasp_classify` | Grasp an object and classify it by tactile feedback |
## Usage
For detailed instructions on data loading, environment setup, and benchmarking protocols, please visit our:
👉 [official website](https://univtac.github.io/)
👉 [Github repo](https://github.com/univtac/UniVTAC)
# UniVTAC 基准数据集(UniVTAC Benchmark Dataset)
UniVTAC 基准数据集提供了面向触觉驱动机器人操控任务的仿真数据。
## 概述
本数据集每个任务包含100个任务回合,8个多样化操控任务总计800个任务回合。
## 任务集
目前,UniVTAC 基准数据集涵盖以下具备触觉感知能力的操控任务:
| 任务名称 | 模块标识 | 任务描述 |
|---|---|---|
| **收集** | `collect` | 采集富含接触信息的触觉数据以用于预训练 |
| **举升瓶子** | `lift_bottle` | 抓取并将瓶子从墙面附近的台面上提起 |
| **举升圆柱罐** | `lift_can` | 抓取并提起圆柱形罐子 |
| **插入HDMI接口** | `insert_HDMI` | 将HDMI连接器插入对应接口 |
| **高精度孔轴插入(peg-in-hole)** | `insert_hole` | 高精度孔轴插入装配任务 |
| **插入管件** | `insert_tube` | 将管件插入固定夹具 |
| **拔出钥匙** | `pull_out_key` | 从锁具中取出钥匙 |
| **将瓶子放置至货架** | `put_bottle_in_shelf` | 将瓶子摆放到货架上 |
| **抓取与分类** | `grasp_classify` | 通过触觉反馈抓取物体并完成分类 |
## 使用方法
如需获取数据加载、环境搭建以及基准测试流程的详细说明,请访问:
👉 [官方网站](https://univtac.github.io/)
👉 [GitHub 仓库](https://github.com/univtac/UniVTAC)
提供机构:
maas
创建时间:
2026-02-18



