Abstract
In indoor localization scenarios, a sheer coordinate with respect to a basis is insufficient to indicate the users’ situation due to a lack of information about landmarks distributed in the environments. To extract landmarks’ information manually, however, is inefficient and thus vulnerable to changes of the environments. Simultaneous localization and mapping can solve the localization and landmarks’ information extracting problems. This paper presents WalkSLAM, a SLAM solution that estimates both the path taken by the user and the locations of Wi-fi devices in the indoor space, using a smartphone. This solution extends the previous work by introducing human walking patterns into the specific SLAM problem. Experiments demonstrate that the improvement consists of increased efficiency of the particle filter, and hence, of the overall algorithm, and a better estimation of the user’s location and path.
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Acknowledgments
This paper is supported by National Natural Science Foundation of China (61571162), Ministry of Education—China Mobile Research Foundation (MCM20170106).
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Ma, L., Fang, T., Qin, D. (2020). WalkSLAM: A Walking Pattern-Based Mobile SLAM Solution. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_160
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DOI: https://doi.org/10.1007/978-981-13-6504-1_160
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