Robotic Room-Level Localization Using Multiple Sets of Sonar Measurements

In this paper, we aim to achieve robust and cost-effective room-level localization for the indoor mobile robot. It is unrealistic to obtain precise localization information from the sonar sensors because of the sparseness and uncertainty. Our attempts show that the room-level localization can be ach...

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Bibliographic Details
Published in:	IEEE transactions on instrumentation and measurement 2017-01, Vol.66 (1), p.2-13
Main Authors:	Liu, Huaping, Sun, Fuchun, Fang, Bin, Zhang, Xinyu
Format:	Article
Language:	eng
Subjects:	Coding Encoding Indoor mobile robot Localization Mobile robots multiple measurements Performance evaluation Robot sensing systems room-level localization Sensors Sonar Sonar measurements structured sparse coding
Online Access:	Get full text
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Summary:	In this paper, we aim to achieve robust and cost-effective room-level localization for the indoor mobile robot. It is unrealistic to obtain precise localization information from the sonar sensors because of the sparseness and uncertainty. Our attempts show that the room-level localization can be achieved using sonar sensors by accumulating the sonar data to overcome the limitations of sensor performance. To this end, we formulate the room-level localization as a joint sparse coding problem, which encourages the coding vectors to share the common room sparsity, but different locations. We systematically evaluate the performance of the different coding strategies on the collected sonar measurement data set.
ISSN:	0018-9456 1557-9662