Lightweight Topological-Based Map Matching for Indoor Navigation

Abstract

The variety of indoor architectures challenges for map matching. Unlike outdoor map, indoor pedestrian is even expected to walk on wide corridors, large open areas and irregular shapes of interior spaces. In the overview, most of existing digital maps are for GPS-based navigation systems. GPS does not need a previously estimated position to estimate the current one. But in dead reckoning, the present position is the result of propagating the previous estimated one. This makes most of previous outdoor map matching algorithms cannot be used for pedestrian directly without signification modifications. In this paper, we introduce our lightweight topological-based approach to assist pedestrian dead reckoning algorithm in term of reducing the error of determined position and improving user tracking task. We developed a practical complete, self-contained end-to-end system on a Smartphone. This methodology requires simple computations; hence it runs very fast. We conducted different scenario experiments to demonstrate the usability of our system in indoor environment. The evaluation results showed that the map matching error rate is 4.69% in a 42.6m x 29.6m testing area.

Indoor localization for pedestrians with real-time capability using multi-sensor smartphones

“…For example, in addition to WLAN fingerprinting and inertial sensor measurements, the project Lobster (Hafner et al 2013) also uses GNSS to locate first responders. Other real-time pedestrian indoor navigation systems include combinations of the dead reckoning principle and map matching algorithms (Jiang, Le, and Shie 2016), foot-mounted IMU and RFID measurements (Jiménez Ruiz et al 2012), or visual markers and IMU for improved ARbased indoor navigation (Neges et al 2015). Willemsen, Keller, and Sternberg (2015) and Ebner et al (2015) use a graph-based approach for the indoor location with very small low-cost Micro-Electro-Mechanical Systems (MEMS).…”