Indoor human localization using PIR sensors and accessibility map

Tracking human´s location in indoor environments is very import, for it enables a wide range of applications related to robot service, appliance control and other smart home applications. This paper proposed a new, integrated method for indoor human localization based on passive infrared (PIR) sensors and an accessibility map of the indoor environment. The accessibility map reflects human´s visiting habits in that environment, which also contains geometric as well as furniture layout information. First we build the accessibility map based on the human´s visiting habits as the prior knowledge. Then the PIR sensor data is used to estimate the rough position. A more practical binary sensing model is used to model the PIR output. A particle filter fuses the PIR sensor data and the accessibility map information to refine the localization. To evaluate our method´s performance, simulation experiments are carried out. The results showed that the proposed accessibility map-based PIR localization method outperforms the PIR only localization.