算法
A*搜索算法
树遍历
明星(博弈论)
计算机科学
平滑度
运动规划
路径(计算)
拉默-道格拉斯-派克算法
启发式
功能(生物学)
自适应算法
数学优化
数学
人工智能
机器人
数学分析
进化生物学
计算
生物
程序设计语言
作者
Tao Liao,Fan Chen,Yuting Wu,Hongyu Zeng,Sujian Ouyang,Jian Guan
出处
期刊:Electronics
[MDPI AG]
日期:2024-01-22
卷期号:13 (2): 455-455
标识
DOI:10.3390/electronics13020455
摘要
In response to the shortcomings of the traditional A-star algorithm, such as excessive node traversal, long search time, unsmooth path, close proximity to obstacles, and applicability only to static maps, a path planning method that integrates an adaptive A-star algorithm and an improved Dynamic Window Approach (DWA) is proposed. Firstly, an adaptive weight value is added to the heuristic function of the A-star algorithm, and the Douglas–Pucker thinning algorithm is introduced to eliminate redundant points. Secondly, a trajectory point estimation function is added to the evaluation function of the DWA algorithm, and the path is optimized for smoothness based on the B-spline curve method. Finally, the adaptive A-star algorithm and the improved DWA algorithm are integrated into the fusion algorithm of this article. The feasibility and effectiveness of the fusion algorithm are verified through obstacle avoidance experiments in both simulation and real environments.
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