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Computation of Penetration Between Smooth Convex Objects in Three-Dimensional Space

机译:三维空间中光滑凸对象之间的穿透力计算

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摘要

There are many applications in robotics where collision detection, separation distance, and penetration distance between geometrical models of objects are required. Efficient numerical procedures for the computation of these proximal relations are important as they are frequently invoked. A new measure of penetration and separation called the growth distance has been introduced in the literature. It has been shown that the growth distance can be efficiently computed for convex polytopes. This article extends the computation of growth distance to smooth convex objects. Specifically, we introduce a formulation of the growth distance for smooth convex objects that is well suited for numerical computation. By modeling a convex object as union of convex subob-jects, the growth distance of a wide family of objects can be computed. However, computation of growth distance for such object models may be expensive. A fast algorithm is introduced that reduces the computational time significantly. In the case where the objects undergo continuous relative motions and the growth distances must be evaluated for a large number of closely-spaced points along the motions, further reduction in computational effort is achieved. Numerical experiments with objects that are found in typical robot applications substantiate the claim.
机译:在机器人技术中有许多应用需要碰撞检测,分离距离和物体几何模型之间的穿透距离。计算这些近端关系的有效数值过程很重要,因为它们经常被调用。文献中引入了一种新的渗透和分离度量,称为生长距离。已经表明,对于凸多面体可以有效地计算生长距离。本文将增长距离的计算扩展到光滑凸物体。具体来说,我们介绍了非常适合数值计算的光滑凸物体的增长距离公式。通过将凸对象建模为凸子对象的并集,可以计算出一系列对象的增长距离。但是,针对此类对象模型的增长距离的计算可能很昂贵。引入了一种快速算法,可大大减少计算时间。在物体经历连续的相对运动并且必须针对沿运动的大量紧密间隔的点评估生长距离的情况下,可以进一步减少计算量。在典型的机器人应用中发现的带有对象的数值实验证实了这一主张。

著录项

  • 来源
    《Journal of robotic systems》 |1996年第5期|p.303-315|共13页
  • 作者

    Chong Jin Ong;

  • 作者单位

    Department of Mechanical and Production Engineering National University of Singapore Singapore 0511, Republic of Singapore;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 机器人技术;
  • 关键词

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