Description of field of research:

Indoor positioning has become an important capability for a range of location-based services while the common approaches (Wi-Fi, BLE, IMU, magnetometer) on smartphones are not able to provide seamless and reliable positioning services where GNSS is not available.

Augmented Reality (AR) is a revolutionary technology that can not only implement digital information into the environment but also track the movement of the user in real-time. This makes it a good tool for pedestrian dead reckoning, whose performance can be much better than an IMU-based pedometer’s.

However, a dead reckoning system can only provide relative positioning information and the error will be accumulated over time. The AR technology can be combined with our existing positioning technologies (UWB, BLE) so that an absolute, accurate and continuous positioning service can be achieved at a relatively low cost.


Minerals and Energy Resources Engineering

Research areas

Indoor positioning, Indoor navigation

The candidate will work closely with Dr Binghao Li, Mr Kai Zhao and other team members of the MIoT & IPIN lab with MERE. Mr Kai Zhao is the main contact.

There are AR SDKs available on both iOS and Android platforms (ARKit and ARCore).  It is expected that you can prototype a pedestrian dead reckoning module base on ARCore on the Android platform.

The second task is to quantitatively evaluate the performance of the ARCore dead reckoning in different scenarios (open/close space, clear/crowd environment).

The third task is to improve your module in case of the “kidnapped robot scenario”, level switching and other edge cases.

In addition, you are also encouraged to engage in the sensor fusion algorithm development, which will be used to combine the ARCore with our existing positioning technologies.

  1. Li, Binghao, et al. ""Investigation of indoor positioning technologies for underground mine environments."" IPIN (Short Papers/Work-in-Progress Papers). 2019.
  2. F. Potortì et al., ""The IPIN 2019 Indoor Localisation Competition—Description and Results,"" in IEEE Access, vol. 8, pp. 206674-206718, 2020, doi: 10.1109/ACCESS.2020.3037221.
  3. Feigl, Tobias, et al. ""Localization Limitations of ARCore, ARKit, and Hololens in Dynamic Large-scale Industry Environments."" VISIGRAPP (1: GRAPP). 2020.