Mapping kinematic interactions between objects for robot motion planning

M. Pomarlan
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Abstract

Knowledge about the possible interactions between objects is needed by a robot if it is to plan tasks employing those objects. In this paper, we focus on methods to represent the ways in which the degrees of freedom of a rigid body interlocked with another change as the relative pose of the two objects changes, in such a way so as to allow efficient planning queries about the objects. Narrow passages and occlusions make this a difficult problem for usual approaches in robotics involving sample based planners and 3D shape reconstruction. Instead, we propose a data structure (called a DoF map) that can be constructed from tactile information alone, and which, once constructed for a pair of rigid bodies, enables fast planning queries for that particular pair. The data structure is also sufficiently abstract and allows reuse even for objects with different geometry, as long as the new pair of objects is such that, if its DoF map were constructed, it would be isomorphic to the DoF map of the original pair. The DoF map then provides a possible criterion for object pair classification that is more general than exact geometric shape but more informative than simple topology. We describe a method to construct DoF maps, as well as a method to reuse a known one. We test these ideas in simulation.
机器人运动规划中物体间运动相互作用的映射
如果机器人要计划使用这些物体的任务,就需要了解物体之间可能的相互作用。在本文中,我们重点研究了当刚体与另一个刚体的相对位姿发生变化时,刚体互锁的自由度变化的表示方法,以便对物体进行有效的规划查询。狭窄的通道和闭塞使这成为机器人技术中涉及基于样本的规划和3D形状重建的常规方法的难题。相反,我们提出了一种数据结构(称为DoF map),它可以仅从触觉信息构建,并且一旦为一对刚体构建,就可以对该特定对进行快速规划查询。数据结构也足够抽象,甚至允许对具有不同几何形状的对象进行重用,只要新对象对是这样的,如果构造它的DoF映射,它将与原始对的DoF映射同构。DoF图为对象对分类提供了一个可能的标准,它比精确的几何形状更通用,但比简单的拓扑结构更有信息量。我们描述了一种构造DoF图的方法,以及一种重用已知DoF图的方法。我们在模拟中测试这些想法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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