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GA-based optimization of biped robot gait control of CPG model

机译:基于GA的CPG模型的双层机器人步态控制优化

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As a result of the traditional artificial gait planning is a relatively rigid and slow, the lack of flexible self-organizing capacity, and the real biological differences between gait. Good use of the biological central pattern generator of the self-excited behavior have a rhythm of movement in order to adapt to a variety of coordination in complex environments, this paper, we propose a biological central pattern generator model for the core of the establishment of biped robot control system, and CPG parameter values of the parameters of genetic algorithm for high-performance distinctions, in accordance with the relationship between human movement, the establishment of the knee, hip and ankle joint movement relation equation. By simulation control mechanism based on the CPG rhythm of the biped robot motion control method is effective, bio-gait biped robot, when the realization possible.
机译:由于传统的人工步态规划是一种相对刚性和缓慢的,缺乏灵活的自组织能力,以及步态之间的真实生物差异。良好的使用自我激发行为的生物中心模式发生器具有节奏的运动,以便在复杂环境中适应各种协调,本文提出了一种生物中心模式发电机模型,为建立的核心建立Biped机器人控制系统和CPG参数值的遗传算法的参数,用于高性能区别,根据人体运动的关系,建立膝关节,臀部和踝关节运动方程。通过基于Biped机器人运动控制方法的CPG节奏的仿真控制机制是有效的,生物步态Biped Robot,当实现可能。

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