基于A~*的双向预处理改进搜索算法
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摘要
本文针对传统A~*算法存在冗余路径点较多与单向搜索耗时较长的缺点,提出了一种改进A~*算法.该算法采用双向预处理结构减少冗余节点数,并通过归一化处理和增加节点标记信息进一步优化估价函数提高遍历速度.利用仿真软件对改进A~*算法进行实验,并与其它经典路径规划算法进行比较.仿真结果表明,改进后的A~*算法较于传统A~*算法能以较低的搜索节点数和搜索时长较好的完成全局路径规划.
In this study, an improved A~* algorithm is proposed for the traditional A-star algorithm, which has many redundant path points and long-term one-way search. The proposed algorithm uses a bidirectional preprocessing structure to reduce the number of redundant nodes, and further optimizes the evaluation function to improve the traversal speed by normalizing the processing and adding node marker information. Simulation software is used to simulate the improved A~*algorithm and compare with other classical path planning algorithms. The simulation results show that the improved A~*algorithm can complete the global path planning with lower search node number and search duration than the traditional A~* algorithm.
In this study, an improved A~* algorithm is proposed for the traditional A-star algorithm, which has many redundant path points and long-term one-way search. The proposed algorithm uses a bidirectional preprocessing structure to reduce the number of redundant nodes, and further optimizes the evaluation function to improve the traversal speed by normalizing the processing and adding node marker information. Simulation software is used to simulate the improved A~*algorithm and compare with other classical path planning algorithms. The simulation results show that the improved A~*algorithm can complete the global path planning with lower search node number and search duration than the traditional A~* algorithm.
引文
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19史辉,曹闻,朱述龙,等.A*算法的改进及其在路径规划中的应用.测绘与空间地理信息,2009,32(6):208-211.[doi:10.3969/j.issn.1672-5867.2009.06.070]
2Cormen TT,Leiserson CE,Rivest RL.Introduction to Algorithms.Cambridge:MIT Press,2001.
3Mohajer B,Kiani K,Samiei E,et al.A new online random particles optimization algorithm for mobile robot path planning in dynamic environments.Mathematical Problems in Engineering,2013,2013:491346.
4陆锋,卢冬梅,崔伟宏.交通网络限制搜索区域时间最短路径算法.中国图象图形学报,1999,4(10):849-853.
5Fredman ML,Tarjan RE.Fibonacci heaps and their uses in improved network optimization algorithms.Proceedings of the 25th Annual Symposium on Foundations of Computer Science.Singer Island,FL,USA.1984.
6王士同.双向启发式图搜索算法BFFRA.电子学报,1990,18(6):34-39.[doi:10.3321/j.issn:0372-2112.1990.06.006]
7郑年波,李清权,徐敬海,等.基于转向限制和延误的双向启发式最短路径算法.武汉大学学报·信息科学版,2006,31(3):256-259.
8熊壬浩,刘羽.A*算法的改进及并行化.计算机应用,2015,35(7):1843-1848.
9熊伟,张仁平,刘奇韬,等.A*算法及其在地理信息系统中的应用.计算机系统应用,2007,16(4):14-17.[doi:10.3969/j.issn.1003-3254.2007.04.004]
10王殿君.基于改进A*算法的室内移动机器人路径规划.清华大学学报(自然科学版),2012,52(8):1085-1089.
11张宏烈.移动机器人全局路径规划的研究[硕士学位论文].哈尔滨:哈尔滨工程大学,2002.
12魏宁,刘一松.基于栅格模型的移动机器人全局路径规划研究.微计算机信息,2008,24(11):229-231.[doi:10.3969/j.issn.1008-0570.2008.11.094]
13陈华华,杜歆,顾伟康.基于遗传算法的静态环境全局路径规划.浙江大学学报(理学版),2005,32(1):49-53.[doi:10.3321/j.issn:1008-9497.2005.01.013]
14Chabini I,Lan S.Adaptations of the A*algorithm for the computation of fastest paths in deterministic discrete-time dynamic networks.IEEE Transactions on Intelligent Transportation Systems,2002,3(1):60-74.[doi:10.1109/6979.994796]
15Whangbo TK.Efficient modified bidirectional A*algorithm for optimal route-finding.In:Okuno HG,Ali M,eds.New Trends in Applied Artificial Intelligence.Berlin Heidelberg:Springer,2007:344-353.
16Elbeltagi E,Hegazy T,Hosny AH,et al.Schedule-dependent evolution of site layout planning.Construction Management and Economics,2001,19(7):689-697.[doi:10.1080/01446190110066713]
17Hart PE,Nilsson NJ,Raphael B.Correction to“a formal basis for the heuristic determination of minimum cost paths”.ACM SIGART Bulletin,1972,(37):28-29.
18Guesgen HW,Mitra D.A multiple-platform decentralized route finding system.Proceedings of the 12th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems.Cairo,Egypt.1999.707-713.
19史辉,曹闻,朱述龙,等.A*算法的改进及其在路径规划中的应用.测绘与空间地理信息,2009,32(6):208-211.[doi:10.3969/j.issn.1672-5867.2009.06.070]