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当前位置: 首页 > 文章 > 基于免疫遗传和蚁群融合算法的散乱点云曲面拟合 农业机械学报 2016,47 (12) 424-430
Position: Home > Articles > Scattered Point Clouds Surface Fitting Based on Immune Genetic and Ant Colony Algorithm Transactions of the Chinese Society for Agricultural Machinery 2016,47 (12) 424-430

基于免疫遗传和蚁群融合算法的散乱点云曲面拟合

作  者：
付玮;吴禄慎;陈华伟
单  位：
南昌大学机电工程学院
关键词：
曲面拟合;散乱点云;免疫遗传算法;蚁群算法
摘  要：
对复杂型面物体的曲面拟合方法进行了研究,通过点云数据参数化、基于免疫遗传算法(IGA)的自适应节点计算、反求曲线控制顶点、点云数据分割以及曲面拼接5个步骤来进行曲面拟合。提出了一种基于免疫遗传和蚁群的融合算法,将其应用于曲面拟合中,利用免疫遗传算法的全局搜索能力,来提高蚁群的收敛速度。该算法通过免疫遗传算法的选择、交叉、变异操作、疫苗接种和疫苗选择,并将免疫遗传算法引入到蚁群系统的迭代中,有效地解决了蚁群系统易陷入局部最优和易退化的缺点。采用fender、fandisk、bunny、cow 4个实例,对其3D散乱点云分别采用融合算法、遗传算法(GA)和免疫遗传算法进行曲面拟合,实验表明该融合算法具有很好的收敛速度和全局最优解的搜索能力,通过该算法所拟合的曲面拟合精度较高,相比GA和IGA算法,其拟合精度分别提高18%和11%以上,可以满足复杂型面物体的曲面拟合要求。
译  名：
Scattered Point Clouds Surface Fitting Based on Immune Genetic and Ant Colony Algorithm
作  者：
Fu Wei;Wu Lushen;Chen Huawei;School of Mechanical and Electrical Engineering,Nanchang University;
关键词：
surface fitting;;scattered point cloud;;immune genetic algorithm;;ant colony algorithm
摘  要：
The surface fitting method of complex surface object was researched,which inclued the processes of parameterization of point cloud data,immune genetic algorithm( IGA) based adaptive node calculation,reversing of curve control points,segmentation of point cloud and surface stitching constitute surface fitting. Fusion of immune genetic algorithm and ant colony system fitting algorithm was proposed in surface. The immune genetic algorithm was introduced into the iterative process of each ant colony,and the ability of local optimization and global search ability of immune genetic algorithm can improve the convergence speed of ant colony. In the algorithm,the immune genetic algorithm can effectively overcome the shortcomings of ant colony system which easily trap into local optimal solution or degradation by selecting,intersecting and mutating of genetic algorithm along with the immune vaccination of immune algorithm. The fender,fandisk,bunny and cow of the 3D scattered points cloud were fitted by fusion algorithm,genetic algorithm( GA) and immune genetic algorithm( IGA). The experiments showed that the new algorithm was very excellent in convergence speed and global optimal solution search capability.The fitting surface of this algorithm was better than those of GA and IGA in fitting precision with fitting precision improved by 18% and 11%,respectively,which can meet the requirements of complex curved surfaces.

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