A Strictly Convex Hull for Computing Proximity Distances With Continuous Gradients

被引:38
作者
Escande, Adrien [1 ,2 ]
Miossec, Sylvain [3 ]
Benallegue, Mehdi [4 ]
Kheddar, Abderrahmane [5 ,6 ]
机构
[1] CNRS, Natl Inst Adv Ind Res & Technol, Intelligent Syst Res Inst, Joint Robot Lab,CRT UMI3218, Tsukuba, Ibaraki 3058568, Japan
[2] CNRS AIST JRL UMI3218 CRT, Paris, France
[3] Univ Orleans, PRISME Lab, F-18020 Bourges, France
[4] CNRS, LAAS, F-31031 Toulouse 4, France
[5] CNRS AIST JRL, F-34095 Montpellier, France
[6] Univ Montpellier 2, CNRS, LIRMM, F-34095 Montpellier, France
关键词
Bounding volume; continuous gradients of proximity distances; smooth and nonsmooth optimization; sphere-torus patches; strictly convex hulls; OBJECTS;
D O I
10.1109/TRO.2013.2296332
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
We propose a new bounding volume that achieves a tunable strict convexity of a given convex hull. This geometric operator is named sphere-tori-patches bounding volume (STP-BV), which is the acronym for the bounding volume made of patches of spheres and tori. The strict convexity of STP-BV guarantees a unique pair of witness points and at least C-1 continuity of the distance function resulting from a proximity query with another convex shape. Subsequently, the gradient of the distance function is continuous. This is useful for integrating distance as a constraint in robotic motion planners or controllers using smooth optimization techniques. For the sake of completeness, we compare performance in smooth and nonsmooth optimization with examples of growing complexity when involving distance queries between pairs of convex shapes.
引用
收藏
页码:666 / 678
页数:13
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