ALF: An Autonomous Localization Framework for Self-Localization in Indoor Environments

Eckert J, German R, Dressler F (2011)


Publication Type: Conference contribution

Publication year: 2011

Edited Volumes: 2011 International Conference on Distributed Computing in Sensor Systems and Workshops, DCOSS'11

Pages Range: 1-8

Conference Proceedings Title: Proceedings of 7th IEEE/ACM International Conference on Distributed Computing in Sensor Systems (DCOSS 2011)

Event location: Barcelona ES

URI: http://www7.informatik.uni-erlangen.de/~eckert/publications/pdf/eckert2011alf.pdf

DOI: 10.1109/DCOSS.2011.5982157

Abstract

A lot of algorithms and applications can benefit from position information. GPS localization has become a standard for outdoor usage. But if a higher accuracy is needed or within GPS-denied areas providing this knowledge is still an open and nontrivial topic. Especially for unknown or dynamic environments. In this paper we propose a framework which is capable of autonomously exploring unknown environments in a fully decentralized way. It provides accurate and real-time localization support for customers. The usual very time intensive manual deployment and position assignment of reference nodes is avoided. Additional we show that the algorithm can detect and handle Non Line of Sight (NLOS) issues which is a very important criteria for real world applications. © 2011 IEEE.

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APA:

Eckert, J., German, R., & Dressler, F. (2011). ALF: An Autonomous Localization Framework for Self-Localization in Indoor Environments. In Proceedings of 7th IEEE/ACM International Conference on Distributed Computing in Sensor Systems (DCOSS 2011) (pp. 1-8). Barcelona, ES.

MLA:

Eckert, Jürgen, Reinhard German, and Falko Dressler. "ALF: An Autonomous Localization Framework for Self-Localization in Indoor Environments." Proceedings of the 7th IEEE/ACM International Conference on Distributed Computing in Sensor Systems (DCOSS 2011), Barcelona 2011. 1-8.

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