• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Engineering Computations >Optimal stable gait for nonlinear uncertain humanoid robot using central force optimization algorithm
【24h】

Optimal stable gait for nonlinear uncertain humanoid robot using central force optimization algorithm

机译：基于中心力优化算法的非线性不确定类人机器人的最佳稳定步态

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Purpose The purpose of this paper is to design a novel optimized biped robot gait generator which plays an important role in helping the robot to move forward stably. Based on a mathematical point of view, the gait design problem is investigated as a constrained optimum problem. Then the task to be solved is closely related to the evolutionary calculation technique. Design/methodology/approach Based on this fact, this paper proposes a new way to optimize the biped gait design for humanoid robots that allows stable stepping with preset foot-lifting magnitude. The newly proposed central force optimization (CFO) algorithm is used to optimize the biped gait parameters to help a nonlinear uncertain humanoid robot walk robustly and steadily. The efficiency of the proposed method is compared with the genetic algorithm, particle swarm optimization and improved differential evolution algorithm (modified differential evolution). Findings The simulated and experimental results carried out on the small-sized nonlinear uncertain humanoid robot clearly demonstrate that the novel algorithm offers an efficient and stable gait for humanoid robots with respect to accurate preset foot-lifting magnitude. Originality/value This paper proposes a new algorithm based on four key gait parameters that enable dynamic equilibrium in stable walking for nonlinear uncertain humanoid robots of which gait parameters are initiatively optimized with CFO algorithm.
机译：目的本文的目的是设计一种新颖的，优化的两足机器人步态发生器，它在帮助机器人稳定前进方面起着重要作用。基于数学观点，将步态设计问题作为约束的最佳问题进行了研究。然后要解决的任务与进化计算技术密切相关。设计/方法/方法基于这一事实，本文提出了一种新的方法来优化人形机器人的两足动物步态设计，该方法允许以预设的抬脚幅度稳定踩踏。新提出的中心力优化（CFO）算法用于优化两足动物的步态参数，以帮助非线性不确定类人机器人稳健行走。将该方法的效率与遗传算法，粒子群优化算法和改进的差分进化算法（改进的差分进化）进行了比较。研究结果在小型非线性不确定类人机器人上进行的仿真和实验结果清楚地表明，就准确预设的抬脚幅度而言，该新算法为类人机器人提供了一种有效且稳定的步态。独创性/价值本文提出了一种基于四个关键步态参数的新算法，该算法使非线性不确定类人机器人能够在稳定步行中实现动态平衡，其步态参数已通过CFO算法主动优化。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号