Redundant robots are desired to execute multitasks with different priorities simultaneously. The task priorities are necessary to be transitioned for complex task scheduling of whole-body control (WBC). Many methods focused on guaranteeing the control continuity during task priority transition, however either increased the computation consumption or sacrificed the accuracy of tasks inevitably. This work formulates the WBC problem with task priority transition as an Hierarchical Quadratic Programming (HQP) with Recursive Hierarchical Projection (RHP) matrices. The tasks of each level are solved recursively through HQP. We propose the RHP matrix to form the continuously changing projection of each level so that the task priority transition is achieved without increasing computation consumption. Additionally, the recursive approach solves the WBC problem without losing the accuracy of tasks. We verify the effectiveness of this scheme by the comparative simulations of the reactive collision avoidance through multi-tasks priority transitions.
翻译:冗余机器人希望同时执行具有不同优先事项的多任务。 任务优先事项必须转换为全体控制的复杂任务时间安排( WBC ) 。 许多方法侧重于保证任务优先过渡期间的控制连续性, 但要么增加计算消耗量, 要么不可避免地牺牲任务的准确性。 这项工作将任务优先过渡问题与任务优先过渡形成为具有分级分级投影( RHP ) 矩阵。 每个级别的任务通过 HQP 循环解决。 我们建议 RHP 矩阵形成对每个级别不断改变的预测, 以便在不增加计算消耗量的情况下实现任务优先过渡。 此外, 循环方法在不丧失任务的准确性的情况下解决WBC问题。 我们通过对通过多任务优先过渡来进行反应式碰撞避免的比较模拟来核查这个计划的有效性 。