Instrumentation of biomimetic strain sensors in walking robots

运动是动物生存的关键组成部分，必须具有适应性才能持续成功。这种适应性对于行走的昆虫以依赖于任务的方式克服复杂和多变的地形是必要的。昆虫的六条腿由局部和拱形网络协调和控制，这些网络控制每个肢体和肢体关节，这种模块化结构为系统创造了必要的灵活性。运动网络由模式生成中间神经元、运动神经元、肌肉和感觉器官组成。感觉器官监测运动输出，并向其他网络组件提供动态修改和强化反馈。钟形感受器是大多数肢体节段上发现的感觉器官，类似于脊椎动物的高尔基肌腱器官。CS编码高度动态的菌株，这些菌株通过角质层传播。不同的品系在不同的行为中出现。例如，当一条腿在行走过程中在站姿和摆动阶段之间切换时，腿会暴露在随时间变化的各种拉力中。不同肢体上的CS可以监测这些紧张力和力率随时间的变化，它们的反馈可以修改或加强肌肉输出，以确保协调运动和稳定。最近，我用电子显微镜观察了CS的外部形态。这些实验表明，CS的数量和位置在个体和腿部之间存在差异。然后，我使用纳米计算机断层摄影术将形态数据与建模相结合，强调了CS的详细结构在整个角质层分配力中的作用。在一系列平行的实验中，我专注于CS的神经成分，使用光遗传操作来研究CS如何影响腿部运动和协调。在这样做的过程中，我演示了CS的小子集对于这些行为是充分和必要的。这强调了CS对于腿的运动学和时间协调的重要性。这些发现为全面了解本体感觉信息在黑腹毛虫运动网络中的功能提供了生物学基础。这项提议的目标是现在揭示应变测量的力学原理，以及生物力学和神经系统之间的相互作用。我的方法将生物CS知识与机器人仪器相结合，以识别运动行为背景下传感器的结构、位置和方向之间的关系。通过揭示形态和应变感知之间的相互作用，这个项目将揭示昆虫的感觉结构和神经电路如何处理运动过程中遇到的动态力。此外，这些实验将从根本上改变我们对本体感觉应变感知的理解，通过展示角质层结构如何过滤机械感觉信号。

Locomotion is a crucial component of animal survival that has to be adaptable to be consistently successful. This adaptability is necessary for walking insects to overcome complex and changing terrains in a task-dependent manner. The six legs of insects are coordinated and controlled by local and over-arching networks that control each limb and limb joint, and this modular structure creates necessary flexibility in the system. Locomotor networks consist of pattern-generating interneurons, motor neurons, muscles, and sensory organs. Sensory organs monitor the motor output and provide dynamic modifying and reinforcing feedback onto other network components. Campaniform sensilla (CS), sensory organs found on the majority of limb segments, are analogous to the vertebrates' Golgi tendon organ. CS encode highly dynamic strains that spread through the cuticle. Different strains arise during different behaviors. For example, when a leg switches between its stance and swing phase during walking, the leg is exposed to various strains that change over time. CS on different limbs can monitor these tonic forces and the rate of forces changes over time, and their feedback can modify or reinforce muscular output to ensure coordinated movements and stability.Recently, I used electron microscopy to examine the external morphology of CS. These experiments showed that the number and position of CS varied between individuals and legs. I then used nanocomputed tomography to combine the morphological data with modeling, underscoring the role of the detailed structures of the CS in distributing forces across the cuticle. In a parallel series of experiments, I focused on the neural component of the CS, using optogenetic manipulations to investigate how CS affect leg movements and coordination. In doing so, I demonstrated that small subsets of CS are sufficient and necessary for these behaviors. This underlines the importance of CS for kinematic and temporal coordination of the legs. These findings provide the biological basis for a comprehensive understanding of the function of proprioceptive information in the motor networks of D. melanogaster. The goal of this proposal is to now uncover the mechanical principles of strain measurement and the interplay between biomechanics and nervous systems. My approach integrates the biological CS knowledge with robotic instrumentation to identify relationships between the structure, location, and orientation of sensors in the context of movement behavior. By uncovering the interplay between morphology and strain sensing, this project will reveal how insect sensory structures and neural circuits process the dynamic forces encountered during locomotion. Furthermore, these experiments will fundamentally change our understanding of proprioceptive strain sensing by showing how cuticular structures filter mechanosensory signals.