| MECHANICAL ENGINEERING |
|
|
|
|
|
Surface fitting and position-pose measurements based on an improved SA-PSO algorithm |
| LUO Lei1,2, CHEN Ken1, DU Fengpo2, MA Zhenshu2 |
1. Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China;
2. Institute of Ordnance Technology, Shijiazhuang 050000, China |
|
|
|
|
Abstract Scattered point pattern matching is an important issue in computer vision and pattern recognition, which is widely used for target recognition, medical and remote sensing image registration, and position and pose measurements. This paper describes an algorithm for use in an explosive ordnance disposal robot for when the target object is partial exposed. A simulated annealing-particle swarm optimization (SA-PSO) algorithm based on particle density distribution changes for scattered point pattern matching is developed. The algorithm is more accurate and faster than previous algorithms. The fitness function is constructed from a series of scattered points collected from the local surface of a rotated object. Accurate surface fitting and pose parameters are found using coordinate transforms. The factors that affect the accuracy and applicability are discussed in detail. Tests show that this method is accurate and efficient, with less points needed and less sensitivity to point errors compared with the traditional least squares method.
|
| Keywords
particle swarm optimization (PSO) algorithm
simulated annealing (SA)
surface fitting
explosive ordnance disposal (EOD) robot
|
|
|
|
Issue Date: 15 October 2015
|
|
|
[1] 孔新立, 金丰年, 蒋美蓉. 恐怖爆炸袭击方式及规模分析[J]. 爆破, 2007, 24(3): 88-92.KONG Xinli, JIN Fengnian, JIANG Meirong. Analysis of way and scale of terroristic raid [J]. Blasting, 2007, 24 (3): 88-92. (in Chinese)
[2] 范路桥, 姚锡凡, 祁亨年. 排爆机器人的研究现状及其关键技术[J]. 机床与液压, 2008, 36(6): 139-143.FAN Luqiao, YAO Xifan, QI Hengnian. Research progress and key techniques of explosive ordnance disposal robot [J]. Machine Tool & Hydraulics, 2008, 36(6): 139-143. (in Chinese)
[3] 金周英, 白英. 我国机器人发展的政策研究报告[J]. 机器人技术与应用, 2009(2): 1-7.JIN Zhouying, BAI Ying. Policy research report of robot development [J]. Robot Technique and Application, 2009(2): 1-7. (in Chinese)
[4] Jean G V. New robots planned for bomb disposal teams [J]. National Defense, 2011, 96(692): 28-31.
[5] Dakis A. Human presence detection: The navy has tri-service responsibility for EOD-related science and technology development [J]. Chips, 2011, 29(4): 50-52.
[6] ZENG Jianjun, YANG Ruqing, ZHANG Weijun. Research on semi-automatic bomb fetching for an EOD robot [J]. International Journal of Advanced Robotic Systems, 2008, 4(2): 247-252.
[7] Homsup N, Jariyanorawiss T, Homsup W. A control of a bomb disposal robot using a stereo scope vision [C]//IEEE Southeast Con. Huntsville, AL, 2008: 293-294.
[8] 范路桥, 蒋梁中, 汪伟. 排爆机器人双目立体视觉系统的研究和开发[J]. 计算机工程, 2007, 33(7): 207-209.FAN Luqiao, JIANG Liangzhong, WANG Wei. Research and development on explosive-handling robot binocular visual system [J]. Computer Engineering, 2007, 33(7): 207-209. (in Chinese)
[9] 任同群, 赵悦含, 龚春忠. 自由曲面测量的三维散乱点云无约束配准[J]. 光学精密工程, 2013, 21(5): 1234-1243.REN Tongqun, ZHAO Yuehan, GONG Chunzhong. Unconstrained registration of 3-D scattered point clouds for free-form shape measurement [J]. Optics and Precision Engineering, 2013, 21(5): 1234-1243. (in Chinese)
[10] 李二涛, 张国煊, 曾虹. 基于最小二乘的曲面拟合算法研究[J]. 杭州电子科技大学学报, 2009, 29(2): 48-51.LI Ertao, ZHANG Guoxuan, ZENG Hong. Algorithm of surface fitting research based on least-squares methods [J]. Journal of Hangzhou Dianzi University, 2009, 29(2): 48-51. (in Chinese)
[11] Kennedy J, Eberhart R C. Particle swarm optimization [C]// Proc of IEEE International Conference on Neural Networks. Piscataway, NJ: IEEE Service Center, 1995: 1942-1948.
[12] Kirkpatrick S, Gelat C D, Veccbi M P. Optimization by simulated annealing [J]. Science, 1983, 220: 611-680.
[13] Clere M, Kennedy J. The particle swarm-explosion, stability and convergence in a multi-dimension complex space [J]. IEEE Transactions on Evolutionary Computation, 2002, 6(l): 58-73.
[14] 王东霞, 温秀兰, 赵艺兵. 基于CAD模型引导测量的自由曲面定位及轮廓度误差评定[J]. 光学精密工程, 2012, 20(12): 2720-2727.WANG Dongxia, WEN Xiulan, ZHAO Yibing. Localization and profile error evaluation of freeform surface based on CAD model-directed measurement [J]. Optics and Precision Engineering, 2012, 20(12): 2720-2727. (in Chinese)
[15] 廖平. 基于粒子群算法和分割逼近法的复杂曲面轮廓度误差计算[J]. 中国机械工程, 2010, 21(2): 201-205.LIAO Ping. Calculation of complex surface profile errors based on hybrid particle swarm optimization algorithm [J]. Mechanical Engineering of China, 2010, 21(2): 201-205. (in Chinese)
[16] Akemi G, Andres I. A new iterative mutually coupled hybrid GA-PSO approach for curve fitting in manufacturing [J]. Applied Soft Computing, 2013(13): 1491-1504.
[17] CHANG Fengcheng, Huang H C. A refactoring method for cache-efficient swarm intelligence algorithms [J]. Information Sciences, 2012(192): 39-49.
[18] Chang W A, Jinung A, Jae C Y. Estimation of particle swarm distribution algorithms: Combining the benefits of PSO and EDAs [J]. Information Sciences, 2012(192): 109-119.
[19] ZHAO Xiuyang, ZHANG Caiming, XU Li. IGA-based point cloud fitting using B-spline surfaces for reverse engineering [J]. Information Sciences, 2013(245): 276-289.
[20] Akemi G, Andres I. Particle swarm optimization for non-uniform rational B-spline surface reconstruction from clouds of 3D data points [J]. Information Sciences, 2012 (192): 174-192.
[21] Craig J. Introduction to Robotic: Mechanics and Control [M]. 3rd Ed. Englewood Cliffs, NJ: Prentice Hall, 2005: 48-71.
[22] 王建录, 刘学云, 廖平. 结合分割逼近和粒子群法的燃气轮机叶片轮廓度误差计算[J]. 西安交通大学学报, 2010, 40(7): 42-45.WANG Jianlu, LIU Xueyun, LIAO Ping. Profile error calculation for gas turbine blade based on subdivision approach algorithm and particle swarm optimization [J]. Journal of Xi'an Jiaotong University, 2010, 40(7): 42-45. (in Chinese) |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
2015,
Vol. 55
