The Robot Joint Torque Measurements for Accidental Collisions and Intentional Contacts
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This dataset contains the joint toque measurements of a robot manipulator (KUKA LWR4+) under accidental collisions and intentional contacts. It is specifically intended for the research study on robot collision detection, classification, diagnosis, or prediction. The dataset was recorded at Chair of Automatic Control Engineering, Technical University of Munich, Munich, Germany, by Dr. Zengjie Zhang, under the supervision of Dr. Dirk Wollherr, in 2017. Its detailed recording procedure is explained in the following work: [1] Zhang Z, Qian K, Schuller B W, and Wollherr D. An online robot collision detection and identification scheme by supervised learning and bayesian decision theory[J]. IEEE Transactions on Automation Science and Engineering, 2020, 18(3): 1144-1156. The dataset contains a number of external signal pieces of three classes: accidental collision (cls), with intentional manual contacts (ctc), and free from contacts (fre). Each signal piece lasts for 1.024s subject to the sampling rate 1kHz. Collisions or contacts occur at 0.256s of the signal pieces. The unit of the signal measurement is Nm. All the signals are recorded for the seven joints (#1 to #7) of the KUKA robot arm. The dataset is stored in .csv files. Each .csv file, containing the torque signal pieces for each class and each joint, is formed as an N by M matrix, where M = 1024 is the length of the signals and N is the number of signal pieces of the corresponding classes. For 'cls', N = 6960; for 'ctc', N = 7583; and for 'fre', N = 14098. Refer to the 'ReadMe.md' file for how to import the data to Python or MATLAB. This dataset is openly accessible for research work. Please cite this dataset and reference [1] if you publish the work based on them.
本数据集包含KUKA LWR4+机械臂在意外碰撞与有意接触场景下的关节扭矩测量数据，专为机器人碰撞检测、分类、诊断或预测相关研究设计。 本数据集于2017年由曾杰张博士在德国慕尼黑工业大学自动控制工程讲席组、德克·沃勒尔博士的指导下完成录制，详细录制流程可参见下述文献： [1] ZHANG Z, QIAN K, SCHULLER B W, WOLLHERR D. 基于监督学习与贝叶斯决策理论的在线机器人碰撞检测与识别方案[J]. IEEE自动化科学与工程汇刊, 2020, 18(3): 1144-1156. 本数据集包含三类关节扭矩信号片段：意外碰撞类（cls）、有意手动接触类（ctc）以及无接触类（fre）。单条信号片段时长为1.024秒，采样率为1千赫兹（1kHz），碰撞或接触事件发生于信号片段的第0.256秒时刻。信号测量单位为牛米（Nm），所有数据均采集自该KUKA机械臂的7个关节（编号#1至#7）。 本数据集以逗号分隔值（CSV）格式存储，每个CSV文件对应单一类别与单一关节的扭矩信号片段，数据组织为N×M矩阵：其中M=1024为单条信号的采样点数，N为对应类别下的信号片段总数。其中意外碰撞类（cls）的信号片段数N=6960，有意手动接触类（ctc）N=7583，无接触类（fre）N=14098。 若需了解如何将数据导入Python或MATLAB环境，请参考数据集附带的ReadMe.md文件。本数据集面向科研工作者公开获取，若基于本数据集发表研究成果，请同时引用本数据集与上述文献[1]。
