The localization of autonomous vehicles requires, accurate tracking of its position and orientation in all conditions. As modern cities evolve localization would require a more precise accuracy that up to the level of centimetre and decimetre. One of the most crucial struggles in global positioning system and inertial navigation fusion is that the accuracy of the algorithm is reduced during GPS interruptions. In recent days bigdata, machine and deep learning offer great opportunities, especially for future smart and industrial 4.0 autonomous applications. This research programme is aiming to investigate and deploy machine and deep learning approach to improve and reach the level of reliability, accuracy and robustness required at low-cost GPS/IMU unit. The programme will also present a tracking platform solution that would compensates the issues of lack of accuracy in existing localization methods. The initial result of this ongoing programme is presented and reported in this paper. The paper also covers the research programme future development plans and milestones.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 firstname.lastname@example.org
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 email@example.com