摘要
采用遗传算法搜索单步周期和单步步长组成的参数空间获得最优的参数组合,以实现双足机器人稳定和低耗行走。首先是通过基于倒立摆理论规划机器人的各关节位置曲线,来驱动CATIA和ADAMS软件建立机器人三维模型,进而建立稳定性和能效性函数,然后通过均值自适应法实现权重分配来实现两个目标函数的综合,并采用一种新的适应度定义形式设计适应度函数,最后应用遗传算法获得最优解,仿真结果表明,稳定性和能耗性能有了明显的改善。
With the help of genetic algorithm,this paper searches solution space of single-step cycle and single-step length to get optimal parameter combination and realizes biped robot stability and low consumption walk.First based on inverted pendulum theory,the position of each robot joint curve is planned to drive robots 3D model modeled by CATIA and ADAMS.Then with the help of adaptive method,establishes stability and efficiency function and implements the mean weight distribution to achieve two objectives function synthesis,and adopting a new fitness definition to design fitness function.At the last,with the help of genetic algorithm,obtains the optimal solution.Simulation results show that stability and energy performance get obvious improvement.
出处
《武汉理工大学学报》
CAS
CSCD
北大核心
2011年第8期129-132,共4页
Journal of Wuhan University of Technology
基金
国家自然科学基金(50905064)
湖北省自然科学基金(2010CDB01906)
关键词
双足机器人
稳定性
能耗性
遗传算法
biped robot
stability
energy consumption
genetic algorithm
