To economically deploy robotic manipulators the programming and execution of robot motions must be swift. To this end, we propose a novel, constraint-based method to intuitively specify sequential manipulation tasks and to compute time-optimal robot motions for such a task specification. Our approach follows the ideas of constraint-based task specification by aiming for a minimal and object-centric task description that is largely independent of the underlying robot kinematics. We transform this task description into a non-linear optimization problem. By solving this problem we obtain a (locally) time-optimal robot motion, not just for a single motion, but for an entire manipulation sequence. We demonstrate the capabilities of our approach in a series of experiments involving five distinct robot models, including a highly redundant mobile manipulator.
翻译:要在经济上部署机器人操控器,机器人动作的编程和执行必须迅速。 为此,我们提出一种新的、基于约束性的方法,以直观地指定顺序操纵任务,并计算出用于此任务规格的时间最优的机器人动作。 我们的方法遵循基于约束性任务规格的设想, 目标是获得一个基本和以物体为中心的任务描述, 基本上独立于基本机器人运动学。 我们把这个任务描述转换成一个非线性优化问题。 通过解决这个问题, 我们获得了一个( 本地的) 时间最优的机器人动作, 不仅仅是一个动作, 而是整个操作序列。 我们在涉及五个不同的机器人模型的一系列实验中展示了我们的方法能力, 其中包括一个高度冗余的移动操纵器。