High versatility and flexibility of robotic systems require kinematic structures with many degrees of freedom. This usually renders the system kinematically redundant, i.e., the main manipulation or interaction task does not fully determine its maneuvers. Additional constraints or objectives are required to solve the under-determined control and planning problems. The state-of-the-art approaches arrange tasks in a hierarchy and decouple lower from higher priority tasks on velocity or torque level. Velocities and torques are elements of vector spaces. Thus the approaches are inherently based on linear algebra tools. In this paper, we develop an approach to redundancy resolution and decoupling on position level. That requires moving from vector spaces and linear algebra to manifolds and differential geometry. We propose to determine, another set of coordinate functions in addition to the task forward kinematics. The Jacobian of those functions shall resemble the conditions known from the linear algebra-based velocity- and torque-level decoupling to the best extent possible. The approach provides a better insight into the topological properties of robot kinematics and control problems, allowing a more global geometric view. Quasi-decoupled coordinates can help to avoid or diminish some practical and theoretical difficulties related to the classical projection approaches at the cost of higher offline computational efforts. A condition for the existence of these coordinates is derived. If the condition is not satisfied, we still find approximate solutions by numerical optimization. Finally, we show simulation results for both, trajectory tracking and classical impedance control and validate the approach experimentally on a 7DoF robot.
翻译:机器人系统的高度多变性和灵活性要求具有多种自由度的运动结构。 这通常使系统在运动上变得多余, 也就是说, 主操作或互动任务并不完全决定其动作。 需要额外的限制或目标来解决决定不足的控制和规划问题。 最先进的方法将任务排列在一个层次上, 并且从速度或托盘层次的较优先任务中分解较低的任务。 速度和托盘是矢量空间的元素。 因此, 这些方法本质上仍然以线性代数工具为基础。 在本文中, 我们开发了一种系统冗余解和在位置级别上脱钩的方法。 这需要从矢量空间和线性升代数的代数任务完全决定它的动作。 需要从矢量空间和线性代数的代数到不同的几何测量问题。 我们提议确定, 除了前向运动的任务之外, 另一套协调功能的组合, 与线性升数速度和托克水平的计算方法相类似。 因此, 最有可能找到7级级级的解析方法。 这种方法可以更清楚地了解机器人的表层解算方法的表面特性特性特性特性特性, 和精确的精确的计算方法, 使得我们无法避免产生更精确的精确的精确的精确的计算, 。