基于自运动控制的冗余度机器人运动学优化

KINEMATIC OPTIMIZATION OF REDUNDANT ROBOT BASED ON SELF-MOTION CONTROL

基于自运动变量与雅可比矩阵零空间矢量的关系,提出了冗余度机器人自运动变量选取的新方法。基于线性化思想,建立了冗余度机器人运动学性能指标统一的表达式,并推导了性能指标的自运动变量解析式。利用非线性反馈,建立了基于自运动变量的优化控制系统,从而提出了冗余度机器人优化控制的新算法。该算法减少了系统的状态变量,从而简化了优化控制系统,比起以往的优化算法,如梯度投影法等,具有运算量小、优化能力强等优点,特别是在多冗余度机器人控制系统中具有很高的应用价值。利用计算机仿真证实了所提优化方法的可行性。

Based on the relationship between self-motion parameters and Jacobian null-space vectors, a new method for choosing self-motion parameters of redundant robots is proposed. Using linearization principle, an unified formulation of kinematic performance index is established and its analytical form in terms of self-motion parameters is deduced. Using nonlinear feedback, an optimal control system based on self-motion parameters is established. The proposed algorithm is characterized by less computation and great capability of optimization compared with GPM etc. The feasibility of the proposed algorithm is demonstrated by computer simulation results.