Monocular vision-based Simultaneous Localization and Mapping (SLAM) is used for various purposes due to its advantages in cost, simple setup, as well as availability in environments where navigation with satellites is not effective. However, camera motion and map points can be estimated only up to a global scale factor with monocular vision. Moreover, estimation errors accumulate over time without bound, if the camera cannot detect previously observed map points for closing a loop. We propose an innovative approach to estimate a global scale factor and reduce drifts in monocular vision-based localization with an additional single ranging link, easily integrated with the back-end of monocular visual SLAM methods. The performance of the proposed algorithm is validated by experimental testing with a ground vehicle system.      «

Monocular vision-based Simultaneous Localization and Mapping (SLAM) is used for various purposes due to its advantages in cost, simple setup, as well as availability in environments where navigation with satellites is not effective. However, camera motion and map points can be estimated only up to a global scale factor with monocular vision. Moreover, estimation errors accumulate over time without bound, if the camera cannot detect previously observed map points for closing a loop. We propose a...     »