面向深海着陆器全局动态路径规划方法

吕超; 李思念; 刘爽; 潘彬彬

doi:10.13433/j.cnki.1003-8728.20200477

面向深海着陆器全局动态路径规划方法

doi: 10.13433/j.cnki.1003-8728.20200477

吕超^1,,
李思念¹,
刘爽^1, ,,
潘彬彬²

1.
上海海洋大学工程学院, 上海 201306
2.
上海海洋大学海洋科学学院, 上海 201306

基金项目:

国家自然科学基金面上项目 51876114

上海交通大学海洋工程国家重点实验室开放基金项目 1303

上海交通大学海洋工程国家重点实验室开放基金项目 1512

上海海洋可再生能源工程技术研究中心 19DZ2254800

详细信息

作者简介:
吕超(1977-), 副教授, 硕士生导师, 研究方向为海洋工程装备, 海洋渔船与渔业工程, clv@shou.edu.cn

通讯作者:
刘爽, 讲师, s-liu@shou.edu.cn

中图分类号: TP242.6
计量
- 文章访问数: 120
- HTML全文浏览量: 79
- PDF下载量: 18
- 被引次数: 0
出版历程
- 收稿日期: 2020-10-28
- 刊出日期: 2022-10-25

Global Dynamic Path Planning Method for Hadal Lander

LYU Chao^1
,,
LI Sinian¹,
LIU Shuang^{1
, ,},
PAN Binbin²

1.
College of Engineering, Shanghai Ocean University, Shanghai 201306, China
2.
College of Marine Science, Shanghai Ocean University, Shanghai 201306, China

摘要

摘要: 为提升深海着陆器三维路径规划全局最优性与动态避障能力，提出了一种融合改进蚁群算法和人工势场法的全局动态路径规划方法。基于传统蚁群算法，引入路径偏移程度，优化构建启发函数，简化栅格地图并优化搜索空间，提升了蚁群算法在三维路径规划中的收敛响应速度。在此基础上，选取改进蚁群算法产生的全局路径中有效关键点作为连续子目标点，融合人工势场法，构建全局路径规划势场模型函数，在保证全局路径规划较优的基础上，提高了路径的平滑性和局部避障能力。利用实验算例验证了方法的有效性，方法能够为水下仪器、水下机器人、水下设备自主导航的规划与优化提供帮助与参考。
- 深海着陆器 /
- 三维路径规划 /
- 蚁群算法 /
- 人工势场法
Abstract: In order to improve the global optimality and dynamic obstacle avoidance ability of hadal lander 3D path planning, a global dynamic path planning method based on the fusion of improved ant colony optimization and artificial potential field algorithm is proposed. Based on the traditional ant colony algorithm, this paper improves the convergence response speed of the ant colony algorithm in 3D path planning by introducing the degree of path offset, optimizing the construction of heuristic functions, simplifying the grid map and optimizing the search space. On this basis, the key points in the global path generated by the improved ant colony algorithm were selected as continuous suborder punctuation points, and the potential field model function of global path planning by the artificial potential field was constructed. On the basis of ensuring the global optimal path, the smoothness of the path and local obstacle avoidance ability are improved. The effectiveness and superiority of this method were verified by an experimental example, which can provide help and reference for the planning and optimization of autonomous navigation of underwater robots and underwater equipment.
- hadal lander /
- 3D global dynamic path planning /
- ant colony algorithm /
- artificial potential field algorithm

HTML全文

图 1 三维地形图

下载: 全尺寸图片幻灯片

图 2 横向偏移点线距离示意图

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图 3 蚂蚁可搜索空间

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图 4 深海着陆器在势场中的受力方向

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图 5 路径点选取平面示意图

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图 6 融合算法流程图

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图 7 简化后的三维栅格地图

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图 8 蚁群算法三维路径规划

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图 9 改进蚁群算法三维路径规划

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图 10 改进前后蚁群算法最佳个体路径长度变化

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图 11 路径长度对比

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图 12 路径垂向偏移程度对比

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图 13 传统人工势场算法三维路径规划

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图 14 融合算法全局路径规划

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图 15 路径在xoy平面投影

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图 16 融合算法全局动态路径规划

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表 1 主要参数设置

蚁群数量迭代次数 τ₀ ρ ω₁ ω₂

30 200 1 0.2 1 0.7

下载: 导出CSV

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