Robot object grasping and drawer throwing data

<strong>Contents</strong> There are two zip archives included (<em>grasping.zip</em> and <em>throwing.zip</em>), corresponding to two experiments (grasping objects and throwing them in a drawer), both performed with a Toyota HSR. Each archive contains two directories - <em>learning</em> and <em>generalisation</em> - with object-specific learning and generalisation data. For each object, we provide a dump of a MongoDB database, which contains data sufficient for learning the models used in our experiments. <strong>Usage</strong> After unzipping the archives, each database can be restored with the command mongorestore [data_directory_name] This will create a MongoDB database with the name of the directory. Code for processing the data and model learning can be found in our GitHub repository.

<strong>数据集内容</strong> 本数据集包含两个压缩归档文件，分别为<em>grasping.zip</em>与<em>throwing.zip</em>，对应两项实验：物体抓取实验与将物体投入抽屉的实验，两项实验均采用丰田HSR（Toyota HSR）机器人完成。每个归档文件均包含两个子目录——<em>learning</em>与<em>generalisation</em>，分别存储针对特定物体的学习数据与泛化数据。针对每一类物体，我们均提供了MongoDB数据库（MongoDB）的转储文件，其中包含足够支撑本实验所用模型训练的完整数据。<strong>使用方法</strong> 解压归档文件后，可通过执行命令`mongorestore [数据目录名]`恢复每个数据库，该命令将创建一个以该目录名称命名的MongoDB数据库。数据处理与模型训练的相关代码可在本团队的GitHub仓库中获取。