Development of an Integrated IMU, Image Recognition and Orientation Sensor for Pedestrian Navigation

Chris Hide and Tom Botterill

Abstract:	This paper describes a scheme for pedestrian navigation integrating measurements from a foot-mounted IMU with position and orientation updates from computer vision techniques. By mounting an IMU on a user’s foot, the position drift can be substantially reduced since zero velocity updates can be applied every step. However, such a system will still suffer from position drift unless occasional measurements are available from other sensors. This paper describes a novel method for restricting such position drift using an image recognition algorithm. Firstly, a database of images and their locations is constructed over an area of interest. A user then navigates the area using foot-mounted inertial sensors and a video camera. As images are acquired, they are used to search the database of images using the Image Bag-of-Words algorithm. When new images are successfully matched with images in the database, the position from the database is used to update the inertial position using a Kalman filter. Furthermore, when images are successfully matched, orientation updates can be applied by estimating the relative orientation of the two cameras. These measurements can help overcome the limitations of the IMU, in particular the problem with heading drift. The integrated inertial and vision system is demonstrated to provide better than 10m accuracy (typically 1-5m) over a period of 21 minutes, and the paper demonstrates how orientation updates could be applied in the future.
Published in:	Proceedings of the 2010 International Technical Meeting of The Institute of Navigation January 25 - 27, 2010 Catamaran Resort Hotel San Diego, CA
Pages:	250 - 258
Cite this article:	Hide, Chris, Botterill, Tom, "Development of an Integrated IMU, Image Recognition and Orientation Sensor for Pedestrian Navigation," Proceedings of the 2010 International Technical Meeting of The Institute of Navigation, San Diego, CA, January 2010, pp. 250-258.
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