Chen Zhihan, Zheng Yuebing
Materials Science and Engineering Program and Texas Materials Institute, The University of Texas at Austin, Austin, TX 78712, USA.
Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
Sci Adv. 2024 Apr 5;10(14):eadk3914. doi: 10.1126/sciadv.adk3914. Epub 2024 Apr 3.
It is beneficial for collective structures to simultaneously have high persistence to environmental noise and high responsivity to nontrivial external stimuli. However, without the ability to differentiate useful information from noise, there is always a tradeoff between persistence and responsivity within the collective structures. To address this, we propose adaptive time delay inspired by the adaptive behavior observed in the school of fish. This strategy is tested using particles powered by optothermal fields coupled with an optical feedback-control system. By applying the adaptive time delay with a proper threshold, we experimentally observe the responsivity of the collective structures enhanced by approximately 1.6 times without sacrificing persistence. Furthermore, we integrate adaptive time delay with long-distance transportation and obstacle-avoidance capabilities to prototype adaptive swarm microrobots. This research demonstrates the potential of adaptive time delay to address the persistence-responsivity tradeoff and lays the foundation for intelligent swarm micro/nanorobots operating in complex environments.
对于集体结构而言,同时具备对环境噪声的高持久性以及对非平凡外部刺激的高响应性是有益的。然而,若缺乏从噪声中区分有用信息的能力,集体结构内部的持久性和响应性之间总会存在权衡。为解决这一问题,我们受鱼群中观察到的适应性行为启发,提出了自适应时间延迟。该策略通过由光热场驱动并结合光学反馈控制系统的粒子进行测试。通过应用具有适当阈值的自适应时间延迟,我们通过实验观察到集体结构的响应性在不牺牲持久性的情况下提高了约1.6倍。此外,我们将自适应时间延迟与长距离运输和避障能力相结合,制作出了自适应群体微型机器人原型。这项研究证明了自适应时间延迟在解决持久性 - 响应性权衡方面的潜力,并为在复杂环境中运行的智能群体微/纳米机器人奠定了基础。