A Receding Horizon-type Solution of the Inverse Kinematic Task of Redundant Robots

H. Issa, B. Varga, J. Tar
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Abstract

With the exception of specially designed kinematic structures, the inverse kinematic task of redundant robots cannot be solved in “closed form”. Redundancy is often needed to make the arm “dexterous”. In general numerical techniques have to be applied. A typical approach is finding the “differential solution” by formulating the Jacobian of the problem in the first step, and using some generalized inverse that selects a definite solution of the ambiguous set of the possible ones. Each of these solutions suffers from huge joint coordinate time-derivatives in the vicinity of the kinematic singularities that are evaded by “deforming” the original task. A quasi-differential approach was recently elaborated that, though calculates the Jacobian, instead “inverting” it, applies a fixed point iteration that automatically evades the singularities. However, its solution depends on the eigenvalues of the Jacobian, and it was found not “flexible enough” for all practical purposes. The Moore-Penrose solution can be generalized as an optimization task under constraints for quite complex cost functions. The hard constraint in this approach forces the exact solution of the inverse kinematic task when it is possible. Due to it the intent of “minimizing the costs” is “overridden” in the vicinity of the singularities. In the present paper, based on the formal structure of the Receding Horizon Controllers, an alternative solution is suggested that allows flexibility for relaxing the costs and the “hard constraints”, too. Its computational complexity to some extent is reduced via evading the technique of gradient reduction. Simulation results are presented for a 7 DoF robot arm.
冗余机器人逆运动任务的后退水平型解
除了特殊设计的运动结构外,冗余机器人的逆运动任务不能以“封闭形式”求解。为了使手臂“灵巧”,经常需要冗余。一般来说,必须应用数值技术。一种典型的方法是在第一步通过表述问题的雅可比矩阵来找到“微分解”,然后使用一些广义逆来选择可能的模糊集合的确定解。每一种解在运动奇点附近都有巨大的关节坐标时间导数,这是通过“变形”原始任务来避免的。一种准微分方法最近被详细阐述,虽然计算雅可比矩阵,而不是“反转”它,但应用一个自动避开奇点的不动点迭代。然而,它的解依赖于雅可比矩阵的特征值,并且对于所有实际目的来说,它被发现不是“足够灵活”。Moore-Penrose解可以推广为一个在相当复杂的代价函数约束下的优化任务。这种方法的硬约束要求在可能的情况下精确求解逆运动任务。因此,“最小化成本”的意图在奇点附近被“覆盖”了。在本文中,基于后退地平线控制器的正式结构,提出了一种替代解决方案,该解决方案也允许灵活地放松成本和“硬约束”。通过回避梯度约简技术,在一定程度上降低了算法的计算复杂度。给出了一个7自由度机械臂的仿真结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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