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A sampling-based multi-tree fusion algorithm for frontier detection

文献类型：期刊论文

作者Fang Z(方正); Qiao, Wenchuan; Si BL(斯白露)
刊名INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
出版日期2019
卷号16期号:4页码:1-14
关键词Exploration frontier-based rapidly-exploring random tree
ISSN号1729-8814
产权排序1
英文摘要Autonomous exploration is a key step toward real robotic autonomy. Among various approaches for autonomous exploration, frontier-based methods are most commonly used. One efficient method of frontier detection exploits the idea of the rapidly-exploring random tree and uses tree edges to search for frontiers. However, this method usually needs to consume a lot of memory resources and searches for frontiers slowly in the environments where random trees are not easy to grow (unfavorable environments). In this article, a sampling-based multi-tree fusion algorithm for frontier detection is proposed. Firstly, the random tree's growing and storage rules are changed so that the disadvantage of its slow growing under unfavorable environments is overcome. Secondly, a block structure is proposed to judge whether tree nodes in a block play a decisive role in frontier detection, so that a large number of redundant tree nodes can be deleted. Finally, two random trees with different growing rules are fused to speed up frontier detection. Experimental results in both simulated and real environments demonstrate that our algorithm for frontier detection consumes fewer memory resources and shows better performances in unfavorable environments.
WOS关键词STRATEGIES
资助项目National Natural Science Foundation of China[61573091] ; Fundamental Research Funds for the Central Universities[N182608003] ; Fundamental Research Funds for the Central Universities[N172608005] ; Natural Science Foundation of Liaoning Province[20180520006] ; State Key Laboratory of Robotics, China[2018-O08]
WOS研究方向Robotics
语种英语
WOS记录号WOS:000481806100001
资助机构National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; Natural Science Foundation of Liaoning Province ; State Key Laboratory of Robotics, China
源URL[http://ir.sia.cn/handle/173321/25481]  
专题沈阳自动化研究所_机器人学研究室
通讯作者Fang Z(方正)
作者单位1.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
3.Faculty of Robot Science and Engineering, Northeastern University, Shenyang 110819, China
推荐引用方式
GB/T 7714		 Fang Z,Qiao, Wenchuan,Si BL. A sampling-based multi-tree fusion algorithm for frontier detection[J]. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,2019,16(4):1-14.
APA Fang Z,Qiao, Wenchuan,&Si BL.(2019).A sampling-based multi-tree fusion algorithm for frontier detection.INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,16(4),1-14.
MLA Fang Z,et al."A sampling-based multi-tree fusion algorithm for frontier detection".INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 16.4(2019):1-14.

入库方式： OAI收割

来源：沈阳自动化研究所

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