Department of Engineering Mathematics, University of Bristol, BS8 1TW, United Kingdom.
Bioinspir Biomim. 2022 Aug 30;17(5). doi: 10.1088/1748-3190/ac84b7.
Underwater robot sensing is challenging due to the complex and noisy nature of the environment. The lateral line system in fish allows them to robustly sense their surroundings, even in turbid and turbulent environments, allowing them to perform tasks such as shoaling or foraging. Taking inspiration from the lateral line system in fish to design robot sensors could help to power underwater robots in inspection, exploration, or environmental monitoring tasks. Previous studies have designed systems that mimic both the design and the configuration of the lateral line and neuromasts, but at high cost or using complex procedures. Here, we present a simple, low cost, bio-inspired sensor, that can detect passing vortices shed from surrounding obstacles or upstream fish or robots. We demonstrate the importance of the design elements used, and show a minimum 20% reduction in residual error over sensors lacking these elements. Results were validated in reality using a prototype of the artificial lateral line sensor. These results mark an important step in providing alternate methods of control in underwater vehicles that are simultaneously inexpensive and simple to manufacture.
水下机器人的传感具有挑战性，因为环境复杂且嘈杂。鱼类的侧线系统使它们能够在混浊和动荡的环境中稳健地感知周围环境，从而能够执行群体游动或觅食等任务。从鱼类的侧线系统中汲取灵感来设计机器人传感器，可以帮助水下机器人在检查、勘探或环境监测任务中发挥作用。先前的研究设计了模仿侧线和神经末梢的设计和配置的系统，但成本高或使用复杂的程序。在这里，我们提出了一种简单、低成本、仿生传感器，可以检测从周围障碍物或上游鱼类或机器人上脱落的通过的涡旋。我们证明了所使用的设计元素的重要性，并表明与缺乏这些元素的传感器相比，残余误差减少了至少 20%。使用人工侧线传感器的原型在现实中验证了结果。这些结果标志着在为水下车辆提供替代控制方法方面迈出了重要的一步，这些方法既便宜又易于制造。
