基于稀疏A*算法的AUV全局路径规划

陈 实; 刘纯武; 黄芝平; 蔡郭汕

doi:10.11993/j.issn.1673-1948.2012.04.007

基于稀疏A*算法的AUV全局路径规划

doi: 10.11993/j.issn.1673-1948.2012.04.007

国防科技大学机电工程与自动化学院, 湖南长沙, 410073

详细信息

作者简介:
陈实(1986-), 男, 在读硕士, 研究方向为数字化测试技术.

中图分类号: TJ630.33; TP301.6
计量
- 文章访问数: 1989
- HTML全文浏览量: 2
- PDF下载量: 751
- 被引次数: 0
出版历程
- 收稿日期: 2012-01-07
- 修回日期: 2012-03-07
- 刊出日期: 2012-08-20

Global Path Planning for AUV Based on Sparse A* Search Algorithm

College of Mechatronics and Automation, National University of Defense Technology College, Changsha 410073, China

摘要

摘要: 路径规划是自主式水下航行器(AUV)研究领域的重要课题之一。传统的AUV路径规划算法, 如人工势场法、图搜索法等, 容易出现陷入局部最优解、计算速度慢等问题, 为克服上述缺陷, 本文基于稀疏A*算法, 提出了一种新的用于构造搜索空间的随机布点方法, 在路径规划区域内, 利用随机函数均匀地布撒足够多的搜索节点, 从而构成搜索空间, 可显著降低计算量, 提高搜索效率; 并进一步对所得路径进行通视性检查, 有效地减少路径点个数和折点数, 获得更优路径。仿真试验结果验证了该算法的正确性和有效性, 表明该算法具有全局优化能力强、计算速度快的优点, 具有一定的工程应用价值。
- 自主式水下航行器 /
- 路径规划 /
- 稀疏A*算法 /
- 路径优化
Abstract: Classical autonomous underwater vehicle (AUV) path planning algorithms, such as artificial potential field method and graph search algorithm, often result in the problems of easily converging on local optimum and low calcula-tion speed. To solve the problems, a new method for distributing random points is proposed based on the sparse A* search algorithm for constructing search space, where a random function is used to evenly distribute enough search nodes in the path planning area. This method can obviously reduce the calculation work and increase the search effi-ciency. After the original path is deduced, an intervisibility test is conducted to reduce the path turning points and get an optimal path. Simulation result shows that the proposed method is feasible and valid, and it features better global opti-mization and higher calculation speed.
- autonomous underwater vehicle(AUV) /
- path planning /
- sparse A* search algorithm /
- path optimization

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参考文献(10)

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