Xu Nicole W, Townsend James P, Costello John H, Colin Sean P, Gemmell Brad J, Dabiri John O
Department of Bioengineering, School of Engineering and School of Medicine, Stanford University, Stanford, CA 94305, USA.
Graduate Aerospace Laboratories (GALCIT), California Institute of Technology, Pasadena, CA 91125, USA.
Biomimetics (Basel). 2020 Nov 21;5(4):64. doi: 10.3390/biomimetics5040064.
Biohybrid robotic designs incorporating live animals and self-contained microelectronic systems can leverage the animals' own metabolism to reduce power constraints and act as natural chassis and actuators with damage tolerance. Previous work established that biohybrid robotic jellyfish can exhibit enhanced speeds up to 2.8 times their baseline behavior in laboratory environments. However, it remains unknown if the results could be applied in natural, dynamic ocean environments and what factors can contribute to large animal variability. Deploying this system in the coastal waters of Massachusetts, we validate and extend prior laboratory work by demonstrating increases in jellyfish swimming speeds up to 2.3 times greater than their baseline, with absolute swimming speeds up to 6.6 ± 0.3 cm s. These experimental swimming speeds are predicted using a hydrodynamic model with morphological and time-dependent input parameters obtained from field experiment videos. The theoretical model can provide a basis to choose specific jellyfish with desirable traits to maximize enhancements from robotic manipulation. With future work to increase maneuverability and incorporate sensors, biohybrid robotic jellyfish can potentially be used to track environmental changes in applications for ocean monitoring.
结合活体动物和独立微电子系统的生物混合机器人设计，可以利用动物自身的新陈代谢来减少功率限制，并作为具有损伤耐受性的天然底盘和致动器。先前的研究表明，生物混合机器人水母在实验室环境中能够展现出比其基线行为快2.8倍的速度提升。然而，这些结果能否应用于自然动态的海洋环境，以及哪些因素会导致动物个体差异较大，仍然未知。在马萨诸塞州沿海水域部署该系统后，我们通过证明水母游泳速度比基线快2.3倍，绝对游泳速度达到6.6±0.3厘米/秒，验证并扩展了之前的实验室研究。这些实验游泳速度是使用一个水动力模型预测的，该模型的形态学和时间相关输入参数来自实地实验视频。该理论模型可为选择具有理想特性的特定水母提供依据，以最大限度地提高机器人操纵的增强效果。随着未来提高机动性和集成传感器的工作开展，生物混合机器人水母有望用于海洋监测应用中的环境变化跟踪。
