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摘要:
We propose a motion planning gap-based algorithms for mobile robots in an unknown environment for exploration purposes. The results are locally optimal and sufficient to navigate and explore the environment. In contrast with the traditional roadmap-based algorithms, our proposed algorithm is designed to use minimal sensory data instead of costly ones. Therefore, we adopt a dynamic data structure called Gap Navigation Trees (GNT), which keeps track of the depth discontinuities (gaps) of the local environment. It is incrementally constructed as the robot which navigates the environment. Upon exploring the whole environment, the resulting final data structure exemplifies the roadmap required for further processing. To avoid infinite cycles, we propose to use landmarks. Similar to traditional roadmap techniques, the resulting algorithm can serve key applications such as exploration and target finding. The simulation results endorse this conclusion. However, our solution is cost effective, when compared to traditional roadmap systems, which makes it more attractive to use in some applications such as search and rescue in hazardous environments.
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篇名 Gap Navigation Trees for Discovering Unknown Environments
来源期刊 智能控制与自动化(英文) 学科 医学
关键词 MOTION Planning Gap-Navigation Trees ROADMAP ROBOTICS Local Environments
年,卷(期) 2015,(4) 所属期刊栏目
研究方向 页码范围 229-240
页数 12页 分类号 R73
字数 语种
DOI
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研究主题发展历程
节点文献
MOTION
Planning
Gap-Navigation
Trees
ROADMAP
ROBOTICS
Local
Environments
研究起点
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研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
智能控制与自动化(英文)
季刊
2153-0653
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
250
总下载数(次)
0
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