In some outdoor applications, navigating a mobile robots needs to be geo-referenced and with hight precision. For its geo-localization, the mobile robot can use a global positioning system (GPS). This system has an accuracy of 6 to 12 meters for a typical civilian GPS receiver, depending on number of available satellites. This accuracy can be reduced to 1m by using a DGPS (Differential GPS) system which employs a second receiver at a fixed location to compute corrections to the GPS satellite measurements. Another limitation for the use of GPS systems, is the necessity to operate in open aeria where the GPS receiver has permanently access to satellites. This is not always possible, especially in urban environments. This paper introduces a technique based on two Extended Kalman Filters (EKF) for robot localization in geo-referenced maps. One EKF is used to correct the GPS localization based on data from an Inertial Navigation System (INS) and wheels encoders and the second EKF is used for visual Simultaneous localization and Mapping (SLAM). This solution will increase the accuracy and the robustness of the positioning during the outage of GPS system and alows a SLAM in less featured environments.
Original languageEnglish
Title of host publicationIEEE International Conference on Mechatronics (ICM 2011)
Number of pages5
Publication statusPublished - 2011
EventUnknown -
Duration: 1 Jan 2011 → …

Publication series

NameIEEE International Conference on Mechatronics (ICM 2011)


Period1/01/11 → …

    Research areas

  • SLAM, Kalman Filter

ID: 2093888