Localization and Mapping for Indoor Navigation: Survey

Localization and Mapping for Indoor Navigation: Survey

Heba Gaber (Ain-Shams University, Egypt), Mohamed Marey (Ain-Shams University, Egypt), Safaa Amin (Ain-Shams University, Egypt) and Mohamed F. Tolba (Ain-Shams University, Egypt)
Copyright: © 2017 |Pages: 25
DOI: 10.4018/978-1-5225-2229-4.ch007
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Abstract

Mapping and exploration for the purpose of navigation in unknown or partially unknown environments is a challenging problem, especially in indoor environments where GPS signals can't give the required accuracy. This chapter discusses the main aspects for designing a Simultaneous Localization and Mapping (SLAM) system architecture with the ability to function in situations where map information or current positions are initially unknown or partially unknown and where environment modifications are possible. Achieving this capability makes these systems significantly more autonomous and ideal for a large range of applications, especially indoor navigation for humans and for robotic missions. This chapter surveys the existing algorithms and technologies used for localization and mapping and highlights on using SLAM algorithms for indoor navigation. Also the proposed approach for the current research is presented.
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Background

SLAM addresses the problem of acquiring a spatial map of the environment while simultaneously localizing the mobile agent relative to this model (Thrun S., 2008). SLAM and navigation techniques have been covered in many citations, most of them have been applied to autonomous wheeled mobile robots and some of them were applied to smartphones and personal PDAs for human indoor navigation applications that support people with disabilities, firefighting groups and people navigating complex and large buildings.

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