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- Title
Fusion of the SLAM with Wi-Fi-Based Positioning Methods for Mobile Robot-Based Learning Data Collection, Localization, and Tracking in Indoor Spaces.
- Authors
Lee, Gunwoo; Moon, Byeong-Cheol; Lee, Sangjae; Han, Dongsoo
- Abstract
The ability to estimate the current locations of mobile robots that move in a limited workspace and perform tasks is fundamental in robotic services. However, even if the robot is given a map of the workspace, it is not easy to quickly and accurately determine its own location by relying only on dead reckoning. In this paper, a new signal fluctuation matrix and a tracking algorithm that combines the extended Viterbi algorithm and odometer information are proposed to improve the accuracy of robot location tracking. In addition, to collect high-quality learning data, we introduce a fusion method called simultaneous localization and mapping and Wi-Fi fingerprinting techniques. The results of the experiments conducted in an office environment confirm that the proposed methods provide accurate and efficient tracking results. We hope that the proposed methods will also be applied to different fields, such as the Internet of Things, to support real-life activities.
- Subjects
MOBILE learning; ACQUISITION of data; MOBILE robots; SLAM (Robotics); VITERBI decoding; OFFICE environment; DATA collection platforms
- Publication
Sensors (14248220), 2020, Vol 20, Issue 18, p5182
- ISSN
1424-8220
- Publication type
Article
- DOI
10.3390/s20185182