Research Repository

Sensor fusion of camera, GPS and IMU using fuzzy adaptive multiple motion models

Bostanci, Erkan and Bostanci, Betul and Kanwal, Nadia and Clark, Adrian F (2018) 'Sensor fusion of camera, GPS and IMU using fuzzy adaptive multiple motion models.' Soft Computing, 22 (8). pp. 2619-2632. ISSN 1432-7643

1512.02766.pdf - Accepted Version

Download (3MB) | Preview


A tracking system that will be used for augmented reality applications has two main requirements: accuracy and frame rate. The first requirement is related to the performance of the pose estimation algorithm and how accurately the tracking system can find the position and orientation of the user in the environment. Accuracy problems of current tracking devices, considering that they are low-cost devices, cause static errors during this motion estimation process. The second requirement is related to dynamic errors (the end-to-end system delay, occurring because of the delay in estimating the motion of the user and displaying images based on this estimate). This paper investigates combining the vision-based estimates with measurements from other sensors, GPS and IMU, in order to improve the tracking accuracy in outdoor environments. The idea of using Fuzzy Adaptive Multiple Models was investigated using a novel fuzzy rule-based approach to decide on the model that results in improved accuracy and faster convergence for the fusion filter. Results show that the developed tracking system is more accurate than a conventional GPS–IMU fusion approach due to additional estimates from a camera and fuzzy motion models. The paper also presents an application in cultural heritage context running at modest frame rates due to the design of the fusion algorithm.

Item Type: Article
Uncontrolled Keywords: Sensor fusion; Fuzzy adaptive motion models; Camera; GPS; IMU
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 21 Apr 2017 09:01
Last Modified: 23 Sep 2022 18:49

Actions (login required)

View Item View Item