Limbless locomotors, from microscopic worms to macroscopic snakes, traverse complex, heterogeneous natural environments typically using undulatory body wave propagation. Theoretical and robophysical models typically emphasize body kinematics and active neural/electronic control. However, we contend that because such approaches often neglect the role of passive, mechanically controlled processes (i.e., those involving mechanical intelligence), they fail to reproduce the performance of even the simplest organisms. To discover principles of how mechanical intelligence aids limbless locomotion in heterogeneous terradynamic regimes, here we conduct a comparative study of locomotion in a model of heterogeneous terrain (lattices of rigid posts). We use a model biological system, the highly studied nematode worm C. elegans, and a novel robophysical device whose bilateral actuator morphology models that of limbless organisms across scales. The robot's kinematics quantitatively reproduce the performance of the nematodes with purely open-loop control; mechanical intelligence simplifies control of obstacle navigation and exploitation by reducing the need for active sensing and feedback. An active behavior observed in C. elegans, undulatory wave reversal upon head collisions, robustifies locomotion via exploitation of the systems' mechanical intelligence. Our study provides insights into how neurally simple limbless organisms like nematodes can leverage mechanical intelligence via appropriately tuned bilateral actuation to locomote in complex environments. These principles likely apply to neurally more sophisticated organisms and also provide a new design and control paradigm for limbless robots for applications like search and rescue and planetary exploration.

翻译：从微观蠕虫到宏观蛇类，无肢运动体通常依靠波浪式身体传播来穿越复杂、异质的自然环境。理论和机器人物理模型通常强调身体运动学以及主动神经/电子控制。然而，我们认为，由于这些方法常常忽略被动、机械控制过程（即涉及机械智能的过程）的作用，它们甚至无法复现最简单生物体的运动表现。为探索机械智能在异质陆生动力学条件下如何辅助无肢运动，本研究在异质地形的模型（刚性柱阵列）中进行了无肢运动的比较分析。我们采用模型生物系统——被广泛研究的秀丽隐杆线虫，以及一种新型机器人物理装置，其双侧致动器形态模拟了跨尺度的无肢生物体结构。该机器人在纯开环控制下定量复现了线虫的运动表现；机械智能通过减少对主动感知和反馈的需求，简化了障碍物导航与利用的控制。在线虫中观察到的一种主动行为——头部碰撞后的波浪式反向传播——通过利用系统的机械智能增强了运动的鲁棒性。本研究揭示了神经简单的无肢生物（如线虫）如何通过适当调节的双侧致动来利用机械智能在复杂环境中运动。这些原理可能适用于神经更复杂的生物体，也为搜救与行星探测等应用中的无肢机器人提供了新的设计与控制范式。