由增材制造实现的软执行器和机器人

IF 11.2 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Dong Wang, Jinqiang Wang, Zequn Shen, Chengru Jiang, J. Zou, Le Dong, N. Fang, G. Gu
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引用次数: 8

摘要

软机器人系统对人类友好,可以模仿动物的复杂运动,这在各种应用中带来了巨大的潜力,从新型驱动和可穿戴电子设备到在非结构化环境中操作的仿生机器人。由于软材料的使用,传统的刚性材料的制造方法无法用于软机器人。3D打印可以实现材料和结构的个性化和定制,是满足柔性机器人多功能和多材料需求的一种很有前途的制造方法。本文综述了各类软机器人系统的制造方法,并讨论了未来研究的挑战和前景,包括对气动、电驱动、磁驱动和4d打印软执行器以及集成软执行器和传感器的深入讨论。最后,讨论了实现多材料、多尺度、多功能的3d打印软体机器人所面临的挑战。预计《控制、机器人和自主系统年度评论》第14卷的最终在线出版日期是2023年5月。修订后的估计数请参阅http://www.annualreviews.org/page/journal/pubdates。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Soft Actuators and Robots Enabled by Additive Manufacturing
Soft robotic systems are human friendly and can mimic the complex motions of animals, which introduces promising potential in various applications, ranging from novel actuation and wearable electronics to bioinspired robots operating in unstructured environments. Due to the use of soft materials, the traditional fabrication and manufacturing methods for rigid materials are unavailable for soft robots. 3D printing is a promising fabrication method for the multifunctional and multimaterial demands of soft robots, as it enables the personalization and customization of the materials and structures. This review provides perspectives on the manufacturing methods for various types of soft robotic systems and discusses the challenges and prospects of future research, including in-depth discussion of pneumatic, electrically activated, magnetically driven, and 4D-printed soft actuators and integrated soft actuators and sensors. Finally, the challenges of realizing multimaterial, multiscale, and multifunctional 3D-printed soft robots are discussed. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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来源期刊
CiteScore
28.30
自引率
2.20%
发文量
25
期刊介绍: The Annual Review of Control, Robotics, and Autonomous Systems offers comprehensive reviews on theoretical and applied developments influencing autonomous and semiautonomous systems engineering. Major areas covered include control, robotics, mechanics, optimization, communication, information theory, machine learning, computing, and signal processing. The journal extends its reach beyond engineering to intersect with fields like biology, neuroscience, and human behavioral sciences. The current volume has transitioned to open access through the Subscribe to Open program, with all articles published under a CC BY license.
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