Ishimoto Kenta, Moreau Clément, Herault Johann
Research Institute for Mathematical Sciences, Kyoto University, Kyoto 606-8502, Japan.
Nantes Université, École Centrale Nantes, IMT Atlantique, CNRS, LS2N, UMR 6004, Nantes F-44000, France.
J R Soc Interface. 2025 Jan;22(222):20240688. doi: 10.1098/rsif.2024.0688. Epub 2025 Jan 29.
Dissipative environments are ubiquitous in nature, from microscopic swimmers in low-Reynolds-number fluids to macroscopic animals in frictional media. In this study, we consider a mathematical model of a slender elastic locomotor with an internal rhythmic neural pattern generator to examine various undulatory locomotion such as swimming and crawling behaviours. By using local mechanical load as mechanosensory feedback, we have found that undulatory locomotion robustly emerges in different rheological media. This progressive behaviour is then characterized as a global attractor through dynamical systems analysis with a Poincaré section. Furthermore, by controlling the mechanosensation, we were able to design the dynamical systems to manoeuvre with progressive, reverse and turning motions as well as apparently random, complex behaviours, reminiscent of those experimentally observed in . The mechanisms found in this study, together with our dynamical systems methodology, are useful for deciphering complex animal adaptive behaviours and designing robots capable of locomotion in a wide range of dissipative environments.
耗散环境在自然界中无处不在,从低雷诺数流体中的微观游动者到摩擦介质中的宏观动物。在本研究中,我们考虑一个具有内部节律性神经模式发生器的细长弹性运动体的数学模型,以研究各种波动运动,如游泳和爬行行为。通过使用局部机械负载作为机械感觉反馈,我们发现波动运动在不同流变介质中稳健地出现。然后,通过庞加莱截面的动力学系统分析,将这种渐进行为表征为全局吸引子。此外,通过控制机械感觉,我们能够设计动力学系统,使其以渐进、反向和转向运动以及明显随机的复杂行为进行操纵,这让人联想到在实验中观察到的行为。本研究中发现的机制,连同我们的动力学系统方法,有助于解读复杂的动物适应性行为,并设计能够在各种耗散环境中运动的机器人。