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Two-level RRT planning for robotic push manipulation

机译:机器人推式操纵的两级RRT规划

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This paper presents an algorithm for planning sequences of pushes, by which a robotic arm equipped with a single rigid finger can move a manipulated object (or manipulandum) towards a desired goal pose. Pushing is perhaps the most basic kind of manipulation, however it presents difficult challenges for planning, because of the complex relationship between manipulative pushing actions and resulting manipulandum motions. The motion planning literature has well developed paradigms for solving e.g. the piano-mover's problem, where the search occurs directly in the configuration space of the manipulandum object being moved. In contrast, in pushing manipulation, a plan must be built in the action space of the robot, which is only indirectly linked to the motion space of the manipulandum through a complex interaction for which inverse models may not be known. In this paper, we present a two stage approach to planning pushing operations. A global RRT path planner is used to explore the space of possible manipulandum configurations, while a local push planner makes use of predictive models of pushing interactions, to plan sequences of pushes to move the manipulandum from one RRT node to the next. The effectiveness of the algorithm is demonstrated in simulation experiments in which a robot must move a rigid body through complex 3D transformations by applying only a sequence of simple single finger pushes.
机译:本文提出了一种用于计划推动顺序的算法,通过该算法,配备有单个刚硬手指的机械臂可以将操纵对象(或Manipulandum)移向所需的目标姿势。推动也许是最基本的一种操纵方式,但是由于操纵推动动作与所产生的Manipandumum运动之间存在复杂的关系,因此它在计划方面提出了艰巨的挑战。运动计划文献具有解决例如钢琴演奏者的问题,其中搜索直接在要移动的Manipulandum对象的配置空间中进行。相反,在推动操纵中,必须在机器人的动作空间中建立一个计划,该计划仅通过复杂的交互作用而间接链接到manipulandum的运动空间,而反向模型可能未知。在本文中,我们提出了一种用于计划推进操作的两阶段方法。全局RRT路径规划器用于探索可能的Manipulandum配置的空间,而本地推送规划器则利用推送交互的预测模型来计划将Manipulandum从一个RRT节点移动到下一节点的推送序列。该算法的有效性在仿真实验中得到了证明,在仿真实验中,机器人必须通过仅应用一系列简单的单指推动来通过复杂的3D转换来移动刚体。

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