Efficient Collision and Self-Collision Detection for Humanoids Based on Sphere Trees Hierarchies
Efficient Collision and Self-Collision Detection for Humanoids Based on Sphere Trees Hierarchies
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基于球体树层次结构的人形高效碰撞和自碰撞检测
DOI：
10.1109/ichr.2006.321329
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
R. Dillmann
中科院分区：
文献类型：
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作者：
Klaus Steinbach;J. Kuffner;T. Asfour;R. Dillmann
为了有效地进行碰撞检测和最小距离计算，我们提出了一种在一般三维多边形网格上计算紧凑球树层次的算法。我们使用的球树构造方法优化了层次结构中每一层的球心和半径的位置，以完整地包含底层几何。我们加强了层次结构，使其可以应用于关节型机器人的自碰撞和障碍物碰撞检测。最后，我们引入距离范围界限，有效地减少所需的距离计算的总数。其结果是一个更快的算法，在多个网格对象的集合上表现得特别好
We present an algorithm for computing compact sphere tree hierarchies over general 3D polygonal meshes for the purpose of efficient collision detection and minimum distance computation. The sphere tree construction method we use optimizes the location of the sphere centers and radii at each level of the hierarchy to compactly contain the underlying geometry. We enhance the hierarchy construction so that it can be applied to both self-collision and obstacle collision detection for articulated robots. Finally, we introduce distance range bounds that are effective for minimizing the overall number of required distance computations. The result is a faster algorithm that performs particularly well on collections of multiple mesh objects