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:无肢运动器,从微小的蠕虫到宏观的蛇,通过起伏的身体波浪传播遍历复杂,异质的自然环境。理论和机器人模型通常强调身体运动学和主动的神经/电子控制。然而,我们认为,由于这些方法经常忽略被动、机械控制下的过程(即涉及机械智能的那些),它们未能再现即使是最简单的生物的性能。为了发现机械智能如何在异质的地球动力学环境中帮助无肢运动,在这里,我们进行了一个在模型化的异质地形(棱柱体栅格)中的运动比较研究。我们使用一个模型生物系统,高度研究的线虫C. elegans和一种新颖的机器人设备,其双侧致动器形态模拟了不同尺度的无肢生物。机器人的运动学定量地再现了线虫的表现,只需要纯粹的开环控制;机械智能简化了障碍物导航和开发的控制,通过减少主动传感和反馈的需求。在线虫中观察到的一种活跃行为,即在头部碰撞后的起伏波逆转,通过利用系统的机械智能使运动更加稳固。我们的研究提供了关于如何通过适当调节双侧致动以利用机械智能在复杂环境中移动的神经简单的无肢生物如线虫的原则。这些原则可能适用于神经更加复杂的生物,也为无肢机器人的设计和控制范例提供了一个新的范例,例如搜索和救援以及行星探索。