RobustPathFinder: Handling Uncertainty in Indoor Positioning Techniques

摘要

Indoor navigation technologies rely on accurately determining the position of a moving person or robot to guide her actively
\nthrough the building. This cannot be done using GPS because it is indoors. We have been dealing with this problem in the
\ncontext of designing and building a system for helping blind people navigate in public buildings. However, indoor localization
\nbased on RSSI is not very accurate, since the quality of the signal is influenced by many factors that include, for instance, wall
\nreflections or people passing by. The fact that the person is moving also introduces several degrees of uncertainty, including a
\nchanging number and placement of beacons in-range. The challenge is therefore to develop mechanisms to handle uncertainty. In
\nthis paper we propose and evaluate uncertainty-handling mechanisms