软机器人概述

IF 11.2 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
O. Yasa, Yasunori Toshimitsu, M. Michelis, Lewis S. Jones, Miriam Filippi, T. Buchner, Robert K. Katzschmann
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引用次数: 16

摘要

软机器人的灵活性和顺应性使它们在意想不到的变化环境和条件下执行多种任务时,有可能超越传统的刚体机器人。然而,软机器人还没有显示出它们的全部潜力,因为大自然在运动和操纵等几个领域仍然要先进得多。为了了解是什么限制了它们的性能并阻碍了它们从实验室到现实世界的过渡,未来的研究应该集中在理解软机器人设计和操作背后的原理上。此类研究还应考虑复杂材料、精确建模、先进控制和智能行为方面的主要挑战。作为此类研究的起点,本综述通过研究软机器人的高级驱动和传感模式、建模技术、控制策略和学习架构的工作机制,提供了该领域的当前概况。接下来,我们总结了这些方法如何应用于创建复杂的软机器人,并检查了它们的应用领域。最后,我们提供了未来应该首先解决的关键挑战,以推动软机器人真正为我们的社会增加价值。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。
An Overview of Soft Robotics
Soft robots’ flexibility and compliance give them the potential to outperform traditional rigid-bodied robots while performing multiple tasks in unexpectedly changing environments and conditions. However, soft robots have not yet revealed their full potential since nature is still far more advanced in several areas, such as locomotion and manipulation. To understand what limits their performance and hinders their transition from laboratory to real-world conditions, future studies should focus on understanding the principles behind the design and operation of soft robots. Such studies should also consider the major challenges with regard to complex materials, accurate modeling, advanced control, and intelligent behaviors. As a starting point for such studies, this review provides a current overview of the field by examining the working mechanisms of advanced actuation and sensing modalities, modeling techniques, control strategies, and learning architectures for soft robots. Next, we summarize how these approaches can be applied to create sophisticated soft robots and examine their application areas. Finally, we provide future perspectives on what key challenges should be tackled first to advance soft robotics to truly add value to our society. 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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