PERSONAL NAVIGATION: EXTENDING MOBILE MAPPING TECHNOLOGIES INTO INDOOR ENVIRONMENTS
DOI:
https://doi.org/10.5380/bcg.v15i5.17000Keywords:
Multi-sensor Navigation, Dead Reckoning, AI Methods, Human Locomotion Modeling, Image-based Navigation.Abstract
This paper discusses some unconventional methods for indoor-outdoor navigation, based on the integration of self-contained sensors, including GPS, IMU, digital barometer, magnetometer compass, and a human locomotion model. The human
locomotion model is used as navigation sensor and it is handled by Artificial Intelligence (AI) techniques that form an adaptive knowledge-based system (KBS), which is trained during the GPS signal reception, and is used to support navigation under GPS-denied conditions. A complementary technique used in our solution, which facilitates indoor navigation, is the image-based method (Flash LADAR). In this paper, the system design and an example performance analysis in the mixed indoor-outdoor environment are presented.
Downloads
How to Cite
Issue
Section
License
Submission of an original manuscript to the Journal will be taken to mean that it represents original work not previously published, that is not being considered elsewhere for publication.
The BCG allows the author(s) to hold the copyright without restrictions and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
The BCG also allows the authors to retain publishing rights without restrictions.
