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使用BioIn-Tacto传感模块收集的不均表面的触觉纹理数据集.
Maliheh Marzani1, Soheil Khatibi1, Ruslan Masinjila2
1Department of Computer Science, Lakehead University, Orillia, ON, Canada.
Data in brief
|February 11, 2025
概括
研究人员开发了一个新的触觉数据集,使机器人能够使用多传感器信号识别纹理. 此资源有助于机器人操纵和在各种环境中对象识别.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 材料科学 材料科学 材料科学
- 传感器技术 传感器技术
背景情况:
- 类似人类的机器人操纵需要在各种环境中有效的纹理识别.
- 带有触摸传感器的机器人必须在不可预测的设置中使用触摸相关特征识别纹理.
- 先进的纹理分类需要一个全面的数据集机器人探测器和纹理之间的物理相互作用.
研究的目的:
- 从生物启发的多式联接触感传感模块收集的信号中创建一个新的数据集.
- 为了捕捉机器人探测器和12种不同的触觉纹理之间的动态相互作用.
- 为了支持机器人纹理分类和操纵的研究.
主要方法:
- 使用了一个生物灵感的多式联接触觉传感模块.
- 包括压力,加速度,角率和磁场变化在内的信号被记录在130赫兹.
- 12个纹理中的每一个都使用滑动运动探索了25次,总共有300个探索插曲.
主要成果:
- 创建了一个全面的触觉纹理交互数据集.
- 该数据集包括捕获物理接触动态的多传感器信号.
- 数据包括300个探索性情节,跨越12个不同的纹理.
结论:
- 创建的触觉纹理数据集对于对象识别和机器人操纵非常有价值.
- 这一数据集有助于触觉纹理重建和识别任务.
- 它提供了机器人触觉探索中研究时间序列属性的机会.
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