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Manipulation Planning for Deformable Linear Objects

机译:可变形线性对象的操纵规划

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Research on robotic manipulation has mainly focused on manipulating rigid objects so far. However, many important application domains require manipulating deformable objects, especially deformable linear objects (DLOs), such as ropes, cables, and sutures. Such objects are far more challenging to handle, as they can exhibit a much greater diversity of behaviors, and their manipulation almost inevitably requires two robotic arms, or more, performing well-coordinated motions. This paper describes a new motion planner for manipulating DLOs and tying knots (both self-knots and knots around simple static objects) using two cooperating robotic arms. This planner blends new ideas with preexisting concepts and techniques from knot theory, robot motion planning, and computational modeling. Unlike in traditional motion planning problems, the goal to be achieved by the planner is a topological state of the world, rather than a geometric one. To search for a manipulation path, the planner constructs a topologically biased probabilistic roadmap in the configuration space of the DLO. During roadmap construction, it uses inverse kinematics to determine the successive robot configurations implied by the DLO configurations and tests their feasibility. Also, inspired by the real life, the planner uses static “needles” (by analogy to the needles used in knitting) for maintaining the stability of the DLO during manipulation and to make the resulting manipulation plan robust to imperfections in the physical model of the DLO. The implemented planner has been tested both in graphic simulation and on a dual-PUMA-560 hardware platform to achieve various knots, like bowline, neck-tie, bow (shoe-lace), and stun-sail.
机译:迄今为止,机器人操纵的研究主要集中于操纵刚性物体。但是,许多重要的应用领域都需要操纵可变形对象,尤其是可变形线性对象(DLO),例如绳索,电缆和缝线。这样的物体要处理起来更具挑战性,因为它们表现出更大的行为多样性,并且它们的操纵几乎不可避免地需要两个或更多的机械臂来执行协调良好的动作。本文介绍了一种新的运动计划器,该运动计划器使用两个协作的机械臂来操纵DLO和打结(自结和简单静态对象周围的结)。该计划人员将新思想与先前存在的概念和技术融为一体,这些概念和技术来自结理论,机器人运动计划和计算建模。与传统的运动计划问题不同,计划者要实现的目标是世界的拓扑状态,而不是几何状态。为了搜索操纵路径,计划者在DLO的配置空间中构造了拓扑上有偏差的概率路线图。在路线图构建过程中,它使用逆运动学来确定DLO配置所隐含的连续机器人配置,并测试其可行性。同样,在现实生活的启发下,计划人员使用静态“针”(类似于编织中使用的针)来维持DLO在操作过程中的稳定性,并使生成的操作计划对针筒物理模型中的缺陷具有鲁棒性。 DLO。已实施的计划程序已经在图形仿真和双PUMA-560硬件平台上进行了测试,以实现各种结,例如,鲍林,领带,弓(鞋带)和风帆。

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