基于蚁群算法的水下机器人机械臂工作路径优化

林树锋; 王冬姣; 叶家玮; 刘 鲲

doi:10.11993/j.issn.2096-3920.2019.01.008

基于蚁群算法的水下机器人机械臂工作路径优化

doi: 10.11993/j.issn.2096-3920.2019.01.008

华南理工大学土木与交通学院, 广州广东, 510641

基金项目: 国家重点研发计划项目(2016YFC1400202); 广东省科技项目(2015B010919006); 中国博士后面上基金资助(2017M6 22692)

详细信息

作者简介:
林树锋(1993-), 男, 在读硕士, 主要研究方向为水下机器人运动控制

通讯作者:
刘鲲(1986-), 男, 讲师, 主要研究方向为海洋工程结构振动控制, 电子邮箱: kunliu_hit@hotmail.com.

中图分类号: TP241.3; TE58
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- 被引次数: 0
出版历程
- 收稿日期: 2018-08-31
- 修回日期: 2018-11-14
- 刊出日期: 2019-02-28

Working Path Optimization of Manipulator Arm of Underwater Robot Based on Ant Colony Algorithm

School of Civil and Transportation Engineering, South China University of Technology, Guangzhou, 510641, China

摘要

摘要: 为了提高水下机器人机械臂对导管架清污的工作效率, 缩短电机持续高负荷工作的时间, 在采用声呐回波数据识别工作区域附着物分布图的基础上, 分别以工作时间最短和能耗最小为优化目标, 提出基于蚁群算法的机械臂工作路径规划算法。通过MATLAB和PRO/E软件建立机械臂三维运动学模型, 在某一随机附着物分布条件下, 采用以上2种路径优化算法得到相应的优化路径。仿真结果表明, 与传统的扫描路径相比, 文中提出的2种优化算法在满足工作区域范围的前提下, 能提高机械臂2倍以上的工作效率并降低50%的能耗, 证明了该路径优化算法的有效性。
- 水下机器人 /
- 蚁群算法 /
- 路径优化
Abstract: To improve the efficiency of the manipulator arm of an underwater robot for cleaning jackets and to shorten the motor working time under high load, the sonar echo data are used to identify the distribution of attachments onto the working area, and two working path planning algorithms of manipulator arm based on ant colony algorithm is proposed by respectively taking the shortest working time and the minimum energy consumption as the optimization targets. A three-dimensional kinematic model of the manipulator arm is established through the software MATLAB and PRO/E. Two optimal paths are obtained by the proposed algorithms for a certain random attachment distribution. Simulation results show that compared with the traditional scan path, the proposed two working path planning algorithms increase the working efficiency of the manipulator arm by more than 2 times and reduce its energy consumption by 50% under the premise of satisfying the range of working area, verifying the feasibility of the two proposed path planning algorithms.
- underwater robot /
- ant colony optimization /
- path optimization

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参考文献(7)

[1]	魏羲. 浅谈海洋生物污损对导管架平台安全的影响[J].全面腐蚀控制, 2015, 29(2): 55-57. Wei Xi. Discussion on the Influence of Marine Biofouling of Jacket Platform Security[J]. Total Corrosion Control, 2015, 29(2): 55-57.
[2]	付宜利, 李志海. 爬壁机器人的研究进展[J]. 机械设计, 2008, 25(4): 1-5. Fu Yi-li, Li Zhi-hai. Researching Headway of Wall-Climbing Robots[J]. Journal of Machine Design, 2008, 25(4):1-5.
[3]	Mel Siegel. Remote and Automated Inspection: Status and Prospects[C]//The First Join DoD/FAA/NASA Conference on Aging Aircraft. Ogden UT: DoD/FAA/NASA Conference on Aging Aircraft, 1997.
[4]	汤渭霖. 声呐目标回波的亮点模型[J]. 声学学报, 1994, 19(2): 92-100. Tang Wei-lin. Highlight Model of Echoes from Sonar Targets[J]. Acta Acustica, 1994, 19(2): 92-100.
[5]	朱利超, 魏鹏举, 高杰, 等. 基于亮点模型的水下目标近程回波仿真研究[J]. 舰船电子工程, 2011, 31(11): 153-155. Zhu Li-chao, Wei Peng-ju, Gao Jie, et al. Simulation of Echoes from Underwater Scaling Targets in Short Range Based on Highlight Model[J]. Ship Electronic Engineering, 2011, 31(11): 153-155.
[6]	Denavit J, Hartenberg R S. A Kinematic Notation for Lower Pair Mechanisms Based on Matrices[J]. ASME Journal of Applied Mechanics, 1955, 77(6): 215-221.
[7]	吴庆洪, 张颖, 马宗民. 蚁群算法综述[J]. 微计算机信息, 2011, 27(9): 1-2, 5. Wu Qing-hong, Zhang Ying, Ma Zong-min. Review of Ant Colony Optimization[J]. Control & Automation, 2011, 27(9): 1-2, 5.