[1]郭书杰,田 华,王 伟.一种复杂场景下的路径规划问题解决方法[J].计算机技术与发展,2022,32(03):27-33.[doi:10. 3969 / j. issn. 1673-629X. 2022. 03. 005]
　GUO Shu-jie,TIAN Hua,WANG Wei.A Solution to Path Planning Problems in Complex Scenarios[J].,2022,32(03):27-33.[doi:10. 3969 / j. issn. 1673-629X. 2022. 03. 005]
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一种复杂场景下的路径规划问题解决方法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
32
期数:
2022年03期
页码:
27-33
栏目:
人工智能
出版日期:
2022-03-10

文章信息/Info

Title:
A Solution to Path Planning Problems in Complex Scenarios
文章编号:
1673-629X(2022)03-0027-07
作者:
郭书杰; 田 华; 王 伟
大连东软信息学院 智能与电子工程学院,辽宁 大连 116023
Author(s):
GUO Shu-jie; TIAN Hua; WANG Wei
School of Electronic Engineering,Dalian Neusoft University of Information,Dalian 116023,China
关键词:
路径规划; 路径压缩; 关键点; 子路径; RRT-connect
Keywords:
path planning; path compression; key point; sub-paths; RRT-connect
分类号:
TP301
DOI:
10. 3969 / j. issn. 1673-629X. 2022. 03. 005
摘要:
路径规划在诸多领域都有重要的应用价值,研究者们提出了多种解决路径规划问题的算法。 但复杂场景下的路径规划问题 并未得到很好的解决, 特别是窄通道和 Z 字形场景下的路径规划问题。 为了解决这一问题, 提出了一种关键点路径规划方法。 该方法通过关键点的引入,将整个路径规划切分成多个较短的子路径规划,从而降低问题的规模,提高规划效率;同时, 这些关键点将随机路径搜索转化为启发式搜索,从而大幅提高了在窄通道和 Z 字形下的路径规划效率。算法首先确定绕过障碍物的关键点,然后使用这些关键点引导规划过程,初步规划出一条路径。 最后通过路径压缩来优化路径,降低路径长度。 实验结果表明,该方法不仅能够高效地完成窄通道场和 Z 字形场景中的路径规划,在其他常见场景的应用中也有不俗的表现。
Abstract:
Path planning has valuable application in many fields. Researchers have proposed a variety of algorithms to solve the path planning problem. However,the problem of path planning in complex scenes has not been well solved,especially? ? ?in narrow channel and zigzag scenes. For this,a key point path planning ( KPP) algorithm is proposed. Through the introduction of key points,the whole path planning is divided into several shorter sub-path planning,which reduces the scale of the problem and improves the planning efficiency.At the same time,these key points transform random path search into a heuristic one, so as to greatly improve the efficiency of path planning in narrow channel and zigzag. In the proposed approach,key points are selected near the vertices of obstacles that obstruct the straight line connection of the start and goal points. Sub -paths between key points are created and connected to form an initial path,which is then optimized through path compression for reducing the path length. Experiment shows that the KPP algorithm can not only efficiently complete path planning in narrow channel fields and zigzag scenes,but also has good performance in other common scenes.

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更新日期/Last Update: 2022-03-10