用于机器人大面积触觉传感的数据驱动电阻断层成像技术

IF 7.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Science China Information Sciences Pub Date : 2024-08-19 DOI:10.1007/s11432-023-4130-3
Wendong Zheng, Huaping Liu, Xiaofeng Liu, Fuchun Sun
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引用次数: 0

摘要

本文提出了一种用于大面积触觉传感的新型 DDERT 传感方法。具体而言,该方法利用生成模型将 ERT 传感器的边界测量电压重构为触觉图像。为了提高触觉成像的质量,模型中加入了空间注意机制。此外,还引入了遮罩约束作为先验信息,以确保生成的图像在与物体接触的区域包含更准确的触觉信息。实验结果验证了所提出的方法对于大面积机器人触觉传感是有效的。此外,还制作了基于 ERT 的触觉传感器原型,并在实际机器人应用中对其传感性能进行了评估。
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Data-driven electrical resistance tomography for robotic large-area tactile sensing

In this article, a novel DDERT sensing method is proposed for large-area tactile sensing. In particular, the method utilizes a generative model to reconstruct the boundary measurement voltage of the ERT sensor into a tactile image. To improve the quality of tactile imaging, a spatial attention mechanism is incorporated into the model. Additionally, a mask constraint is introduced as prior information to ensure that the generated images contain more accurate tactile information in areas of contact with objects. Experimental results validate the proposed method is effective for the large-area robotic tactile sensing. Furthermore, the prototype of the ERT-based tactile sensor is fabricated and the sensing performance is evaluated in real robotic applications.

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来源期刊
Science China Information Sciences
Science China Information Sciences COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
12.60
自引率
5.70%
发文量
224
审稿时长
8.3 months
期刊介绍: Science China Information Sciences is a dedicated journal that showcases high-quality, original research across various domains of information sciences. It encompasses Computer Science & Technologies, Control Science & Engineering, Information & Communication Engineering, Microelectronics & Solid-State Electronics, and Quantum Information, providing a platform for the dissemination of significant contributions in these fields.
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