Navigation in the Cities
The aim of the overall concept is the evaluation and usage of low-cost sensors (MEMS) for pedestrian navigation. This includes the testing and improvement of the navigation by optimal integration of the sensor data from the small INS/GPS with other sensors (e.g. cameras and GIS) as well as developing an own Kalman Filter. The core of the indoor-navigation systems is the positioning. The key point of our evaluations is on the transition of outdoor- to indoor- scenarios. We are focussing on a solution without usage of infrastructure sensors. Further questions such as the optimization of routes and destination guidance or the design and setup of map databases for pedestrians will be taken into account later on.
Entering a building is of special interest for the pedestrian navigation. A stabilization of the navigation within buildings can be realized by infrastructure sensors (WLAN, Bluetooth, iGPS, RFID, etc.) which need of course a higher effort. Anyway, they will be used for tests and simulations to stabilze the positioning. To improve the navigation within buildings, GIS data will be combined in the positioning process and also used for guidance. Here, not only the ground plan of the building but also the utilisation of the premises and most frequently used corridors are applied to support the navigation process. In addition further sensors will be used, e.g. Cameras.
In the first period the Xsens MTi-G low-cost INS is used for testing and development. Later on a real strapdown will be implemented on a smartphone environment (e.g. Android). Further sensors as 3 axes MEMS gyroscopes, accelerometer and barometer of good quality have to be added for a prototype to be connected via USB interface. The man-machine interface will be developed in cooperation with the colleagues from urban planning. They are also doing research and evaluation of information that is needed by end users for such a kind of pedestrian navigation system.
Funding: HCU DigitalCity Research Group
