Human-inspired robotic grasping of flat objects
Human-inspired robotic grasping of flat objects
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DOI：
10.1016/j.robot.2018.07.005
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发表时间：
2018-10-01
影响因子：
4.3
通讯作者：
Doulgeri, Zoe
中科院分区：
文献类型：
--
作者：
Sarantopoulos, Iason;Doulgeri, Zoe
在本文中，我们提出了一种用于抓取放置在平面支承表面上的家用平板物体的人工启发的框架。特别提出了三种抓取策略，从不同的场景中抓取较小的平面物体。该框架使用机械手、支撑面和目标对象的表示，封装了场景的粗略信息。此外，该策略通过与支撑面建立柔顺联系来利用支撑面的环境约束，从而提高了对物体几何不确定性以及感知系统可能引入的位姿估计误差的鲁棒性。这是受人类如何通过使用与支撑面的柔顺接触来执行具有对象姿势和几何不确定性的相对抓取任务的启发。最后，通过使用当前场景表示的决策过程来确定策略选择。(C)2018爱思唯尔B.V.保留所有权利。
In this paper, we propose a human-inspired framework for grasping domestic flat objects placed on planar support surfaces. In particular, three grasp strategies are proposed which aim to pinch small flat objects from different scenes. The framework uses representations of the robotic hand, the support surface and the target object which encapsulate rough information for the scene. Furthermore, the strategies exploit the environmental constraint of the support surface by establishing compliant contact with it, which leads to increased robustness against object geometry uncertainties as well as pose estimation errors possibly introduced by the perception system. This is inspired by how humans perform relative grasping tasks with object pose and geometry uncertainties by using compliant contact with the support surfaces. Finally, the strategy selection is determined by a decision making procedure which uses the current scene representation. (C) 2018 Elsevier B.V. All rights reserved.