Human SLAM: Simultaneous Localisation and Configuration (SLAC) of Indoor Wireless Sensor Networks and theri Users

Bulten, W.

Human SLAM: Simultaneous Localisation and Configuration (SLAC) of Indoor Wireless Sensor Networks and theri Users

Files

Bulten, W.,_MA-Thesis_2015.pdf (5.18 MB)

Authors

Bulten, W.

Issue Date

2015-08-24

Language

en

URI

http://theses.ubn.ru.nl/handle/123456789/264

Abstract

The indoor localisation problem, in smart spaces, is more than just finding the whereabouts of users. Finding positions of users relative to the devices of a smart space is even more important. Unfortunately, configuring such systems manually is a tedious process, requires expert knowledge and is not resilient to changes in the environment. We propose a new system, called Simultaneous Localisation and Configuration (SLAC), to address these two challenges, locating the user and the devices, and combine them into a single estimation problem. The SLAC algorithm, which is based on FastSLAM, is able to locate devices using the received signal strength indicator (RSSI) of devices and motion data from users. Simulations have been used to show two main effects on the localisation performance: the amount of RSSI updates and the location of devices in the space. Live tests, in nontrivial environments, showed that we can achieve room level accuracy and that the localisation can be performed in real time. This is all done locally, i.e. running on a user's device, with respect for privacy and without using any prior information of the environment or device locations. More work is required to increase accuracy in larger environments and to make the algorithm more robust for environment noise caused by walls and other objects. Existing techniques, such as map fusing, could alleviate these problems.