Title: Study on the use of Q-R Codes as Landmarks for Indoor Positioning: Preliminary Results
Author(s): Zheqi Li, Jidong Huang
Published in: Proceedings of IEEE/ION PLANS 2018
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 1270 - 1276
Cite this article: Li, Zheqi, Huang, Jidong, "Study on the use of Q-R Codes as Landmarks for Indoor Positioning: Preliminary Results," Proceedings of IEEE/ION PLANS 2018, Monterey, CA, April 2018, pp. 1270-1276.
Full Paper: ION Members/Non-Members: 1 Download Credit
Sign In
Abstract: Indoor positioning, as often needed by mobile robots operating indoor and in other indoor navigation applications, usually has to be obtained without access to GNSS (Global Navigation Satellite Systems) signals. Many indoor localization techniques, such as RF-beacon-based ones and SLAM (Simultaneous Localization and Mapping) techniques, are either susceptible to tampering, environmental noise, or are costly. Alternatively, indoor landmarks, either permanent ones such as doors, windows and light fixtures or human-introduced ones such as pictures and QR codes, can be identified through image processing techniques and used to determine a user’s location based on known landmark locations. This paper explored how to use the high-definition RGB camera and the depth sensor of the Kinect to detect the QR-code-based landmarks and measure the distance to the QR codes, so that it can assist a robot or other user to navigate in indoor environment. The RGB camera of the Kinect sensor was used to capture the images of the QR codes attached on the wall in different locations in the room. Each one of this QR codes has unique identifier and was coded to contain the indoor reference location information. Then the ZBar open-source barcode reading algorithm was applied to decode the QR codes and extract the reference coordinate information within the QR codes. After that, the depth sensor of the Kinect was initiated to measure the distance from the Kinect sensor to these QR codes. These raw data collected from the RGB camera and the depth sensor were calibrated and then used to locate the position of the Kinect within the indoor coordinate frame. In this paper, the preliminary results from testing the algorithm to locate the stationary position of the Kinect sensor using QR codes were presented.