摘要
由于传统人工规划产生步态是比较僵硬,缓慢的,缺乏灵活的自组织能力,与真正生物步态存在很大差异;而生物能很好利用中枢模式发生器的自激行为产生有节律的协调运动从而适应多种复杂环境,但普通CPG控制策略又会使关节间出现抖动,影响步态的控制效果;文中提出了以生物中枢模式发生器模型为核心建立双足机器人控制系统,并对CPG的参数进行遗传算法的高效优化,提高了系统性能,消除了关节的抖动;通过MATLAB仿真验证基于GA参数优化的CPG控制机理的双足机器人节律运动控制方法是有效的,并得到了很好的控制效果。
The traditional artificial gait planning is relatively rigid and slow, the lack of flexible self-organizing capacity causes 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.
出处
《计算机测量与控制》
CSCD
北大核心
2011年第10期2441-2443,共3页
Computer Measurement &Control
关键词
中枢模式发生器
双足机器人
步态控制策略
GA参数优化
节律运动
central pattern generator
biped robot
gait control strategy
GA parameter optimization
rhythmic movement
