Indoor Navigation Systems

Despite indoor activities occupy daily life, pedestrian navigation systems don't work well yet due to the out of GPS signals in indoor. Also, these system can't satisfy wide variety of pedestrians' demands (eg. Avoiding a rain, barrier-free route, brighter street at night to keep a safety, and so on.) We research not only the navigation functions to meet the above issues, but also mapping technologies and improving UI and UX.

Indoor localization system

In indoor which is out of GPS signals, the other sensors are employed such as Wi-Fi, BLE (Bluetooth Low Energy,) Infrared rays, ultrasonic sounds, visible light communications. However, we still haven't got a silver bullet.

We expect the high accurate indoor localization system which consist with low maintenance cost.

We have researched localization methods which estimate not only absolute position but also relative position of a known position by utilizing accelerometer, gyro sensor, and magnetometer those are already install in a smart phone to prevent the additional cost.

Mapping technology

Navigation systems also require accurate maps. Computer aided mapping system is desired to decrease the maintenance cost of the detailed indoor map. Map style is not only 2D but also picture based panoramic view like Google Street View, and 3D.

We have achieved to build whole panoramic map and barrier-free network data of whole Osaka-Umeda underground city. Though, these method are still semi-automatic, we are researching fully automated mapping technologies by using robots or participatory sensing.


Although, most of the map interface of indoor navigation systems are based on 2D maps, there are a lot of research to make the other interfaces.

We have already provided the panoramic viewer system for Osaka-Umeda underground city. Then we are researching other intuitive AR (Augmented Reality) navigation interfaces by using see through HMD (Head Mounted Display) to realize safety navigation system which is not required to switch the direction of head against the smart phone interface.

Especially, to realize AR navigation system, it's important to estimate user's position and the direction of the user's head by utilizing sensor fusion technologies.


  • Rei Okumura, Ismail Arai, Yutaro Atarashi, Kaoru Kawabata, Kazutoshi Fujikawa, “Feasibility Study of Magnetism-based Indoor Positioning Methods in an Incineration Plant,” 2022 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp.563--568, March, 2022, doi: 10.1109/PerComWorkshops53856.2022.9767331. [IEEE Xplore]
  • Genki Terai, Ismail Arai, Kazutoshi Fujikawa, “Fixed point observation of geomagnetism for dynamic fingerprinting map construction, ” Student Workshop, MobiCASE 2018, Japan, March, 2018. [PDF]
  • Ismail Arai, Maiya Hori, Norihiko Kawai, Yohei Abe, Masahiro Ichikawa, Yusuke Satonaka, Tatsuki Nitta, Tomoyuki Nitta, Harumitsu Fujii, Masaki Mukai, Soichiro Horimi, Koji Makita, Masayuki Kanbara, Nobuhiko Nishio and Naokazu Yokoya, “Pano UMECHIKA: A crowded underground city panoramic view system,” The proceedings of the International Symposium on Distributed Computing and Artificial Intelligence 2010 (DCAI '10), pp.174--181, Valencia, Spain, September, 2010. [Springer Link]
  • Ismail Arai, Soichiro Horimi and Nobuhiko Nishio, “Wi-Foto2: Heterogeneous device controller using Wi-Fi positioning and template matching,” Demo, Pervasive 2010, pp.70--73, Helsinki, Finland, May, 2010. [PDF]