Lock Maker: Improving Room-level Localization Using Spatial Constraints
Date Issued
2007
Date
2007
Author(s)
Lee, Shih-Wei
DOI
en-US
Abstract
We discover that it is easy to provide incorrect room-level information which is transformed from the absolute position, although the accuracy of the current RSSI location system is about two meters. Indoor localization researchers have a consensus that systems at least need to provide room-level accuracy. Thus, we propose a spatial constraint model, called Lock Maker and combine it into particle filter to provide better room-level location estimation. In Lock Maker, Space Model constructs the map organization by recording the connection between different regions. Then, Spatial Constraint gives limitations to particles while they
are moving. At the same time, we update limitations by observing the weight of particles distribute over different areas. Region-level Sensor Model uses a longer duration of location information to help change limitations in Spatial Constraints and guide particles to a more suitable position than current.
In our experiments, we compare Lock Maker with Walking Area approach, and Collision Detection Algorithm. The result shows that Lock Maker is more reliable to provide room-level information. Although this approach causes some delay, but we think that the delay is still tolerable to users.
Subjects
室內定位
房間準確度
indoor localization
particle filter
room-level
Type
thesis
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