An Integrated Strategy for Soft Robotics: Wireless Sensing Enabled by Laser-Sintered Silver

IF 8.2 2区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Jiale Lin, Guifang Shao, Dezhi Wu and Qibin Zhuang*, 
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引用次数: 0

Abstract

Soft robots with integrated wireless self-sensing capabilities hold transformative potential for complex environmental exploration and confined-space applications. However, conventional integrated sensing methods force a trade-off between mechanical compliance and precise locomotion monitoring, making wireless, real-time, and high-fidelity locomotion sensing challenging. Here, we present an integrated strategy combining programmable magnetic actuation, laser-sintered flexible strain sensors, and wireless signal transmission to achieve precise, untethered deformation monitoring. Template-assisted magnetization is used to generate spatially resolved magnetic domains, while energy-modulated laser sintering directly fabricates strain sensors on elastomeric substrates. The results show that high-power laser sintering (30 W at 10 mm/s) produces porous silver architectures optimal for strain sensing, with high linearity (±3.2% error) and robust cyclic stability (resistance drift <3.7%). Validation on a tripodal crawling robot reveals that a miniaturized 433 MHz wireless system enables real-time deformation monitoring with a latency of 120 ± 15 μs. This innovative wireless sensing integration opens a paradigm for closed-loop control and adaptive behavior in dynamically deforming soft robots, establishing a scalable framework for embodied intelligence in next-generation robotic systems.

Abstract Image

Abstract Image

软机器人的集成策略:激光烧结银实现无线传感
具有集成无线自感知能力的软体机器人在复杂环境探索和密闭空间应用中具有变革性潜力。然而,传统的集成传感方法必须在机械顺应性和精确的运动监测之间进行权衡,这使得无线、实时和高保真的运动传感具有挑战性。在这里,我们提出了一种集成策略,结合可编程磁驱动、激光烧结柔性应变传感器和无线信号传输,以实现精确的、不受约束的变形监测。模板辅助磁化用于产生空间分辨磁畴,而能量调制激光烧结则直接在弹性体衬底上制造应变传感器。结果表明,高功率激光烧结(30 W, 10 mm/s)产生的多孔银结构最适合应变传感,线性度高(±3.2%误差),循环稳定性强(电阻漂移<;3.7%)。在一个三足爬行机器人上的验证表明,一个小型化的433 MHz无线系统可以实时监测变形,延迟为120±15 μs。这种创新的无线传感集成为动态变形软机器人的闭环控制和自适应行为开辟了一个范例,为下一代机器人系统的具身智能建立了一个可扩展的框架。
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来源期刊
ACS Applied Materials & Interfaces
ACS Applied Materials & Interfaces 工程技术-材料科学:综合
CiteScore
16.00
自引率
6.30%
发文量
4978
审稿时长
1.8 months
期刊介绍: ACS Applied Materials & Interfaces is a leading interdisciplinary journal that brings together chemists, engineers, physicists, and biologists to explore the development and utilization of newly-discovered materials and interfacial processes for specific applications. Our journal has experienced remarkable growth since its establishment in 2009, both in terms of the number of articles published and the impact of the research showcased. We are proud to foster a truly global community, with the majority of published articles originating from outside the United States, reflecting the rapid growth of applied research worldwide.
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