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首页> 外文期刊>Mechatronics, IEEE/ASME Transactions on >Evolutionary-Optimized Central Pattern Generator for Stable Modifiable Bipedal Walking
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Evolutionary-Optimized Central Pattern Generator for Stable Modifiable Bipedal Walking

机译:进化优化的中央模式生成器,用于稳定的可修改双足行走

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摘要

In this paper, an evolutionary-optimized central pattern generator (CPG) considering equality constraints is proposed for stable modifiable bipedal walking. The proposed CPG generates the position trajectories of the swing foot and the center of pelvis in the Cartesian coordinate system at single and double support phases. The significance of the proposed CPG is that it can change the sagittal and lateral step lengths just before the beginning of each single support phase while maintaining the desired values of single and double support times, which are set in the beginning of bipedal walking. To deal with environmental perturbations, the sensory feedbacks in the CPG are designed using the force sensing resistors such that the bipedal robot can maintain its balance. For the optimized parameters of the CPG, a two-phase evolutionary programming is employed. The effectiveness of the method is demonstrated by computer simulation with the Webots model of a small-sized humanoid robot, HSR-IX, and the experiment with HSR-IX developed in the RIT Laboratory, KAIST, Daejeon, Korea.
机译:在本文中,提出了一种考虑等式约束的进化优化中央模式生成器(CPG),用于稳定的可修改双足步行。拟议中的CPG可以在单支撑阶段和双支撑阶段生成笛卡尔坐标系中的摆动脚和骨盆中心的位置轨迹。建议的CPG的意义在于,它可以在每个单支撑阶段开始之前改变矢状和横向步长,同时保持在双足步行开始时设置的单支撑和双支撑时间的理想值。为了应对环境干扰,CPG中的感官反馈是使用力感测电阻器设计的,从而使两足机器人可以保持其平衡。对于CPG的优化参数,采用了两阶段进化规划。该方法的有效性通过使用小型人形机器人HSR-IX的Webots模型进行计算机仿真以及在韩国大田KAIST的RIT实验室开发的HSR-IX进行的实验来证明。

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