Abstract
Since a RGB-D sensor provides rich information about the scene, various object recognition schemes and low-level image descriptors can be used to improve the SLAM performance. However, a cleaning robot, which is usually flat and thus the camera is close to the floor, usually only has a partial view of the objects in front of the camera; therefore, conventional object recognition schemes based on the complete view of objects are not suitable. To address this problem, we introduce a novel object surface recognition algorithm based on the proposed surface component ratio histogram (SCRH). SCRH is a surface descriptor which describes the geometrical shape of the partial view of the object. Without any pre-trained model of the objects, SCRH provides a way to deal with the unexpected objects which the robot encounters during the navigation. SCRH was evaluated using several objects lying on the floor of which the identities are not known in advance. The experimental results show that objects are successfully discriminated based on their surfaces and SCRH is robust for object surface recognition.
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 callMore From: International Journal of Control, Automation and Systems
Disclaimer: 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.
