Crowdsourcing-based indoor mapping using smartphones: A survey

被引:29
|
作者
Zhou, Baoding [1 ,2 ]
Ma, Wei [3 ]
Li, Qingquan [1 ,4 ,5 ,6 ]
El-Sheimy, Naser [7 ]
Mao, Qingzhou [8 ]
Li, You [9 ]
Gu, Fuqiang [10 ]
Huang, Lian [11 ]
Zhu, Jiasong [1 ,2 ]
机构
[1] Shenzhen Univ, Coll Civil & Transportat Engn, Shenzhen 518060, Peoples R China
[2] Shenzhen Univ, Inst Urban Smart Transportat & Safety Maintenance, Shenzhen 518060, Peoples R China
[3] Chongqing Jiaotong Univ, Sch Civil Engn, Chongqing 400074, Peoples R China
[4] Shenzhen Univ, Guangdong Key Lab Urban Informat, Shenzhen 518060, Peoples R China
[5] Shenzhen Univ, MNR Key Lab Geoenvironm Monitoring Great Bay Area, Shenzhen 518060, Peoples R China
[6] Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China
[7] Univ Calgary, Dept Geomat Engn, Calgary, AB T2N 1N4, Canada
[8] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430072, Peoples R China
[9] Wuhan Univ, State Key Lab Surveying Mapping & Remote Sensing, Wuhan 430072, Peoples R China
[10] Chongqing Univ, Coll Comp Sci, Chongqing 400044, Peoples R China
[11] Shenzhen Escope Intelligence Technol Co LTD, Shenzhen, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Indoor mapping; Crowdsourcing; Smartphone; Survey; SIMULTANEOUS LOCALIZATION; MAP CONSTRUCTION; LOCATION; FUTURE; SENSOR; RECONSTRUCTION; POINTS; DESIGN; STATE; BIM;
D O I
10.1016/j.isprsjprs.2021.05.006
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Indoor map is a fundamental element of indoor location-based services (ILBS). However, traditional indoor mapping techniques are labor-intensive and time-consuming. The advancement of smartphones offers great opportunities for crowdsourcing-based indoor mapping, which is one of the most promising applications due to its low cost and flexibility. Over the last decade, many crowdsourcing-based indoor mapping solutions using smartphones have been proposed. This article provides a systematic review of these works. Different from former surveys, we classify the indoor mapping process by the stage of map construction. In particular, we highlight the two key steps, geospatial-element acquisition, and indoor-map construction, and provide state-of-the-art techniques on these topics. Then, we systematically review the crowdsourcing-based indoor mapping solutions under grid-based, landmark-based, and semantic maps. In addition to covering the principles, benefits, and challenges, these systems are compared in terms of sensors, participation, output, experimental environment, and reported accuracy. Besides these existing performance criteria, we extract quantitative performance criteria that are suitable to evaluate crowdsourcing-based indoor mapping solutions. Finally, we present open issues and future research directions.
引用
收藏
页码:131 / 146
页数:16
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