Knowledge Commons of Institute of Automation,CAS
A high-efficiency, information-based exploration path planning method for active simultaneous localization and mapping | |
Li, Peng1,2; Yang, Cai-yun1; Wang, Rui1; Wang, Shuo1,2,3 | |
发表期刊 | INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS |
ISSN | 1729-8814 |
2020 | |
卷号 | 17期号:1页码:14 |
摘要 | The efficiency of exploration in an unknown scene and full coverage of the scene are essential for a robot to complete simultaneous localization and mapping actively. However, it is challenging for a robot to explore an unknown environment with high efficiency and full coverage autonomously. In this article, we propose a novel exploration path planning method based on information entropy. An information entropy map is first constructed, and its boundary features are extracted. Then a Dijkstra-based algorithm is applied to generate candidate exploration paths based on the boundary features. The dead-reckoning algorithm is used to predict the uncertainty of the robot's pose along each candidate path. The exploration path is selected based on exploration efficiency and/or high coverage. Simulations and experiments are conducted to evaluate the proposed method's effectiveness. The results demonstrated that the proposed method achieved not only higher exploration efficiency but also a larger coverage area. |
关键词 | Active SLAM exploration information-based simultaneous localization and mapping path planning |
DOI | 10.1177/1729881420903207 |
关键词[WOS] | SLAM ; FRAMEWORK ; HARDWARE |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Beijing Science and Technology Project[Z181100003118006] ; National Natural Science Foundation of China[61773378] ; National Natural Science Foundation of China[U1713222] ; National Natural Science Foundation of China[61703401] ; Foundation for Innovative Research Groups of the National Natural Science Foundation of China[61421004] ; Foundation for Innovative Research Groups of the National Natural Science Foundation of China[61421004] ; National Natural Science Foundation of China[61703401] ; National Natural Science Foundation of China[U1713222] ; National Natural Science Foundation of China[61773378] ; Beijing Science and Technology Project[Z181100003118006] |
WOS研究方向 | Robotics |
WOS类目 | Robotics |
WOS记录号 | WOS:000514708100001 |
出版者 | SAGE PUBLICATIONS INC |
七大方向——子方向分类 | 智能机器人 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/38455 |
专题 | 多模态人工智能系统全国重点实验室_智能机器人系统研究 |
通讯作者 | Wang, Shuo |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Zhongguancun East Rd 95, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Chinese Acad Sci, Ctr Excellent Brain Sci & Intelligence Technol, Beijing, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Li, Peng,Yang, Cai-yun,Wang, Rui,et al. A high-efficiency, information-based exploration path planning method for active simultaneous localization and mapping[J]. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,2020,17(1):14. |
APA | Li, Peng,Yang, Cai-yun,Wang, Rui,&Wang, Shuo.(2020).A high-efficiency, information-based exploration path planning method for active simultaneous localization and mapping.INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,17(1),14. |
MLA | Li, Peng,et al."A high-efficiency, information-based exploration path planning method for active simultaneous localization and mapping".INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 17.1(2020):14. |
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