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Topological simultaneous localization and mapping: a survey

Published online by Cambridge University Press:  03 December 2013

Jaime Boal ,
Álvaro Sánchez-Miralles  and
Álvaro Arranz
Jaime Boal*
Affiliation:
Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, Madrid, Spain
Álvaro Sánchez-Miralles
Affiliation:
Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, Madrid, Spain
Álvaro Arranz
Affiliation:
Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, Madrid, Spain
*
*Corresponding author. E-mail: jaime.boal@iit.upcomillas.es
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Summary

One of the main challenges in robotics is navigating autonomously through large, unknown, and unstructured environments. Simultaneous localization and mapping (SLAM) is currently regarded as a viable solution for this problem. As the traditional metric approach to SLAM is experiencing computational difficulties when exploring large areas, increasing attention is being paid to topological SLAM, which is bound to provide sufficiently accurate location estimates, while being significantly less computationally demanding. This paper intends to provide an introductory overview of the most prominent techniques that have been applied to topological SLAM in terms of feature detection, map matching, and map fusion.

Keywords

Mobile robotsSLAMTopological modeling of robotsFeature detectionRobot localization
Type
Articles
Information
Robotica , Volume 32 , Issue 5 , August 2014 , pp. 803 - 821
Copyright
Copyright © Cambridge University Press 2013 

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