Abstract
Mobile robot navigation in unstructured environment is a challenging task due to the uncertain nature of the real world. Navigating using visual landmarks could be a mandatory skill together with the ability of building a representation of the world around the robot. This mapping aptitude should be implemented as an efficient real-time task, even if a large number of elements have to be included in the map itself. To this aim, and to help in localising the robot, a promising technique is given by the Extended Kalman Filter in its interlaced version. The resulting SLAM algorithm, proposed in this paper, has a reduced computational cost preserving, at the same time, a good performance.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
