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Dynamics identification of kinematically redundant parallel robots using the direct search method

机译:直接搜索法在运动学冗余并联机器人中的动力学识别

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摘要

This paper addresses both modeling and dynamics identification of kinematically redundant parallel robots. Based on the Lagrangian equations of the first kind and using the coordinate partitioning method the dynamic equations of the regarded mechanism are derived analytically in a reduced symbolic form. The set of minimal dynamic parameters is automatically obtained thanks to the Lagrange function and the virtual work. The direct pattern search technique is applied to calculate optimal excitation trajectories to obtain reliable dynamic parameters. The direct pattern search technique is further used to identify the dynamic parameters. The proposed algorithms can be applied on both serial and parallel mechanisms in order to solve the parameter identification problem. Exemplarily, the redundant 3-(P)RRR mechanism of the Institute of Mechatronic Systems is introduced and described in detail. In order to achieve kinematic redundancy, a prismatic actuator is added to the structure allowing one base joint to move linearly. As a result, the mechanism can be able to reconfigure its geometry according to different optimization criteria and strategies. Several experimental results demonstrate the effectiveness and, therefore, the capability of the introduced identification procedure.
机译:本文讨论了运动学冗余并行机器人的建模和动力学识别。基于第一类拉格朗日方程,并使用坐标划分方法,以简化的符号形式分析性地推导出所考虑机构的动力学方程。借助Lagrange函数和虚拟功,可以自动获取最小动态参数集。直接模式搜索技术用于计算最佳激励轨迹,以获得可靠的动态参数。直接模式搜索技术还用于识别动态参数。所提出的算法可以同时应用于串行和并行机制,以解决参数识别问题。示例性地,介绍并详细描述了机电系统研究所的冗余3-(P)RRR机制。为了实现运动学冗余,向该结构中添加了一个棱柱形致动器,该致动器允许一个基础接头线性移动。结果,该机制可以根据不同的优化标准和策略重新配置其几何形状。几个实验结果证明了所引入的识别程序的有效性,从而证明了其功能。

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