机器人2013，Vol.35Issue(4)：439-448,10.DOI:10.3724/SP.J.1218.2013.00439
基于超二次曲面模型的3维目标定位算法
Superquadrics Model-based 3D Object Localization Algorithm
摘要
Abstract
For the pose parameter estimation problem of 3D objects in an unorganized point cloud,a 3D object localization algorithm based on superquadrics model is proposed.A normalized radial Euclidean distance of a space point from the 3D object under arbitrary pose is defined by using the part-based superquadrics model of the 3D object.Then a nonlinear objective function for the 3D object pose estimation is established according to the mean square distance between the object surface points and the object in the point cloud,as well as the surface point number and interior point number of the object.By this means,the object localization problem is transformed into an optimization problem of the objective function.Then the invasive weed optimization (IWO) algorithm is adopted to optimize this objective function,and the obtained optimal solution is used as the estimation value of the 3D object pose.Experimental results demonstrate that the proposed algorithm can yield accurate object localization results with a good consistency of pose parameters,and effectively suppress the influence of measurement noises on measurement results.关键词
散乱点云/3维目标定位/超二次曲面/非线性目标函数/入侵性杂草优化Key words
unorganized point cloud/ 3D object localization/ superquadrics/ nonlinear objective function/ invasive weed optimization (IWO)分类
信息技术与安全科学引用本文复制引用
汪霖,曹建福,韩崇昭..基于超二次曲面模型的3维目标定位算法[J].机器人,2013,35(4):439-448,10.基金项目
国家863计划资助项目(2006AA01Z126). （2006AA01Z126）
