Welcome to the InfoSci Platform
Reference Hub2
Localization and Mapping for Indoor Navigation: Survey

Localization and Mapping for Indoor Navigation: Survey

Heba Gaber, Mohamed Marey, Safaa Amin, Mohamed F. Tolba
Copyright: © 2017 |Pages: 25
ISBN13: 9781522522294|ISBN10: 1522522298|EISBN13: 9781522522300
DOI: 10.4018/978-1-5225-2229-4.ch007
Cite Chapter Cite Chapter

MLA

Gaber, Heba, et al. "Localization and Mapping for Indoor Navigation: Survey." Handbook of Research on Machine Learning Innovations and Trends, edited by Aboul Ella Hassanien and Tarek Gaber, IGI Global, 2017, pp. 136-160. https://doi.org/10.4018/978-1-5225-2229-4.ch007

APA

Gaber, H., Marey, M., Amin, S., & Tolba, M. F. (2017). Localization and Mapping for Indoor Navigation: Survey. In A. Hassanien & T. Gaber (Eds.), Handbook of Research on Machine Learning Innovations and Trends (pp. 136-160). IGI Global. https://doi.org/10.4018/978-1-5225-2229-4.ch007

Chicago

Gaber, Heba, et al. "Localization and Mapping for Indoor Navigation: Survey." In Handbook of Research on Machine Learning Innovations and Trends, edited by Aboul Ella Hassanien and Tarek Gaber, 136-160. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-2229-4.ch007

Export Reference

Mendeley
Favorite

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.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.