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

这项基础研究旨在建立一个通用理论，用于设计反馈控制机制，以驱动像鱼一样游泳或像蛇一样爬行的机器人系统。该设计方法将使推进具有敏捷性和能效。控制算法的灵感来自中央模式产生器(CPG)-神经回路，在动物运动过程中命令肌肉收缩来实现有节奏的身体运动。CPG是多个神经元的相互连接，具有简单的个体动力学，表现出一种被视为模式的集体行为。CPGs之所以成为工程应用中的一个有吸引力的对象，是因为它能够自适应地选择适合不同环境的身体振荡模式。这项探索性研究将探索CPG体系结构的潜力，为一种新的系统设计方法提供可行的基础，通过反馈控制实现机械系统的协调振动。理解CPG涌现行为的机理可以为具有新功能的工程系统的创新设计提供中心思想。将局部相互作用与由此产生的全球格局联系起来的理论将有助于识别、预测或避免，例如，电网中的交通拥堵和不稳定。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。这个项目的教育目标是为学生提供一个广泛的动力系统观点，不仅适用于工程机械的设计，也适用于理解生物现象。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来实现，并将研究成果纳入控制工程课程。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向神经科学和控制界广泛传播，以促进跨文化施肥。

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.