English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In this study, unlike in other similar studies, the localization of mobile robots has been realized using an integrated system based on odometry, camera images and the extended Kalman filter. This integrated system was developed to determine the location of the mobile robots in the environment. It is controlled by an interface, designed specifically for this study, based on Robot Operation System. In the designed system firstly the images have been acquired from the overhead camera located in a fixed position. The received images have been processed by image processing algorithm. This way the position and rotation angle of the mobile robot have been measured. The location and the rotation angle have been also estimated using the odometric sensors and the kinematic model of mobile robot. The data obtained by these two methods have been used in extended Kalman filter to achieve a more accurate localization of the mobile robot. In the expanded Kalman filter, the image processing system performs the function of measurement model while the odometric sensors perform the function of state forecasting model. The accuracy of the system and performance have been tested with realistic experiments. The results has shown that the developed new system can be used in professional mobile robot applications.

Localization of Mobile Robot using Odometry, Camera Images and Extended Kalman Filter