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
ISSN1729-8814
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
DOI10.1177/1729881420903207
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
被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
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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