Abstract
AbstractThis paper proposes a novel scheme of extracting the features in the ceiling using an upward-looking camera for SLAM in indoor environments. The conventional approaches based on corner or line features have difficulties in associating adjacent indistinguishable features since their descriptors do not have enough information to distinguish them. Therefore, we used various properties of the objects in the ceiling, such as the distribution of nodes, and size and orientation strength of the region of interest. Also, the similarities among adjacent features are calculated to distinguish between unique and non-unique features. The non-unique features are discarded before they are registered to the feature map. The robustness of the proposed scheme is verified by several experiments using a mobile robot. The extended Kalman filter is used to estimate both robot pose and feature position and orientation, and the experimental results show that the proposed scheme successfully works in various indoor environments.
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.
