Development of an indoor positioning and navigation system using monocular SLAM and IMU

Yu-Ching Mai; Ying-Chih Lai

doi:10.1117/12.2242920

11 July 2016 Development of an indoor positioning and navigation system using monocular SLAM and IMU

Yu-Ching Mai, Ying-Chih Lai

Proceedings Volume 10011, First International Workshop on Pattern Recognition; 100111L (2016) https://doi.org/10.1117/12.2242920
Event: First International Workshop on Pattern Recognition, 2016, Tokyo, Japan

Abstract

The positioning and navigation systems based on Global Positioning System (GPS) have been developed over past decades and have been widely used for outdoor environment. However, high-rise buildings or indoor environments can block the satellite signal. Therefore, many indoor positioning methods have been developed to respond to this issue. In addition to the distance measurements using sonar and laser sensors, this study aims to develop a method by integrating a monocular simultaneous localization and mapping (MonoSLAM) algorithm with an inertial measurement unit (IMU) to build an indoor positioning system. The MonoSLAM algorithm measures the distance (depth) between the image features and the camera. With the help of Extend Kalman Filter (EKF), MonoSLAM can provide real-time position, velocity and camera attitude in world frame. Since the feature points will not always appear and can't be trusted at any time, a wrong estimation of the features will cause the estimated position diverge. To overcome this problem, a multisensor fusion algorithm was applied in this study by using the multi-rate Kalman Filter. Finally, from the experiment results, the proposed system was verified to be able to improve the reliability and accuracy of the MonoSLAM by integrating the IMU measurements.

Citation Download Citation

Yu-Ching Mai and Ying-Chih Lai "Development of an indoor positioning and navigation system using monocular SLAM and IMU", Proc. SPIE 10011, First International Workshop on Pattern Recognition, 100111L (11 July 2016); https://doi.org/10.1117/12.2242920

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KEYWORDS

Cameras

Filtering (signal processing)

Navigation systems

Sensors

Distance measurement

Global Positioning System

Algorithm development

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