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arXiv 2409.03421cs.RO
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F3T:一种面向机器人的具备三维力与温度数学解耦能力的软体触觉单元

F3T: A soft tactile unit with 3D force and temperature mathematical decoupling ability for robots

The Hong Kong University of Science and Technology(香港科技大学);City University of Hong Kong(香港城市大学)

Xiong Yang, Hao Ren, Dong Guo, Zhengrong Ling, Tieshan Zhang, Gen Li, Yifeng Tang, Haoxiang Zhao, Jiale Wang, Hongyuan Chang, Jia Dong, Yajing Shen

AI总结:

本文提出软体触觉单元F3T,通过浮山式多层电容与离子凝胶温度传感薄膜,实现法向压力、全向切向力和温度的解耦测量,并消除温度对电容的干扰,为机器人高级运动控制与自主决策提供支持。

摘要:

人体皮肤展现出感知接触力和环境温度的卓越能力,为精细操作提供了复杂而关键的信息。尽管软体触觉传感器近年来取得进展,但在精确解耦信号方面仍面临重大挑战——具体而言,即将力与方向、温度分离——导致其无法满足机器人的高级应用需求。本研究提出一种多层软体传感器单元(F3T),旨在实现法向压力、全向切向力与温度的隔离测量和数学解耦。我们开发了一种圆形同轴磁性薄膜,其具有浮山式多层电容器结构,有助于在所有方向上实现法向力与切向力的物理解耦。此外,我们在触觉传感器顶部集成了一层基于离子凝胶的温度传感薄膜。该传感器对外部压力和形变具有鲁棒性,能够测量温度,并且关键的是,可以消除由环境温度变化引起的电容误差。这一创新设计实现了多信号的解耦测量,为更高层级的机器人运动控制、自主决策和任务规划的发展铺平了道路。

英文摘要:

The human skin exhibits remarkable capability to perceive contact forces and environmental temperatures, providing intricate information essential for nuanced manipulation. Despite recent advancements in soft tactile sensors, a significant challenge remains in accurately decoupling signals - specifically, separating force from directional orientation and temperature - resulting in fail to meet the advanced application requirements of robots. This research proposes a multi-layered soft sensor unit (F3T) designed to achieve isolated measurements and mathematical decoupling of normal pressure, omnidirectional tangential forces, and temperature. We developed a circular coaxial magnetic film featuring a floating-mountain multi-layer capacitor, facilitating the physical decoupling of normal and tangential forces in all directions. Additionally, we incorporated an ion gel-based temperature sensing film atop the tactile sensor. This sensor is resilient to external pressure and deformation, enabling it to measure temperature and, crucially, eliminate capacitor errors induced by environmental temperature changes. This innovative design allows for the decoupled measurement of multiple signals, paving the way for advancements in higher-level robot motion control, autonomous decision-making, and task planning.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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