Central Pattern Generator (CPG) Control of Locomotion for Adaptive Gait Generation

这项基础研究的目的是建立一个通用的理论，设计反馈控制机制，以驱动机器人系统，像鱼一样游泳或像蛇一样爬行。该设计方法将使推进具有敏捷性和能量效率。控制算法的灵感来自中央模式发生器（CPG）--神经元电路，命令肌肉收缩，以实现动物运动过程中有节奏的身体运动。CPG是多个神经元与简单个体动力学的互连，表现出被视为模式的集体行为。是什么使CPG工程应用的一个有吸引力的对象是它的能力，自适应地选择适合于不同环境的身体振荡的模式。本研究将探讨CPG架构的潜力，以提供一个可行的基础，为新的系统设计方法，以实现协调振荡的机械系统的反馈控制。了解的机制，潜在的涌现行为的CPG可以提供一个中心思想，创新设计的工程系统与新的功能。将局部相互作用与最终的全局模式联系起来的理论将有助于识别、预测或避免交通拥堵和电网不稳定等问题。神经科学和控制工程之间的协同效应将在研究和教育中得到利用。该项目的教育目标是为学生提供广泛的动力系统观点，不仅适用于工程机械的设计，也适用于生物现象的理解。这一目标将通过在团队合作环境中对研究生和本科生进行多学科培训，并将研究成果纳入控制工程课程来实现。研究结果将通过会议报告、期刊出版物、特邀研讨会和辅导讲习班广泛传播给神经科学和控制社区，以加强跨文化的交流。

This basic research aims to establish a general theory for designing feedback control mechanisms to drive robotic systems that swim like fishes or crawl like snakes. The design method will enable propulsion with agility and energy efficiency. The control algorithm is inspired by the central pattern generator (CPG) --- neuronal circuits that command muscle contractions to achieve rhythmic body movements during animal locomotion. The CPG is an interconnection of multiple neurons with simple individual dynamics, exhibiting a collective behavior perceived as a pattern. What makes CPGs an attractive object for engineering applications is its ability to adaptively choose the pattern of body oscillation appropriate for varying environments. This exploratory research will investigate the potential of the CPG architecture to provide a viable foundation for a new system design methodology to achieve coordinated oscillations of mechanical systems by feedback control.Understanding of the mechanisms underlying emergent behaviors of CPGs could provide a central idea for innovative design of engineered systems with new functionalities. A theory that relates local interactions to the resulting global pattern would help identify, predict, or avoid, for instance, traffic congestion and instability in power grids. Synergistic effects between neuroscience and control engineering will be exploited in both research and education. The educational goal of this project is to provide students with a broad dynamical systems view point that applies not only to the design of engineered machines but also to understanding of biological phenomena. The goal will be approached through multidisciplinary training of graduate and undergraduate students in a teamwork environment, and by incorporating research findings into control engineering courses. The results will be broadly disseminated to both neuroscience and control communities through conference presentations, journal publications, invited seminars, and tutorial workshops, to enhance cross-cultural fertilizations.