Abstract
In order to navigate an unknown environment, an autonomous robot must be able to build a map of its surroundings while estimating its position at the same time. This problem is known as SLAM. We propose a SLAM system for stereo cameras which builds a map of objects in a scene. The system is based on the SLAM method S-PTAM and an object detection module. The object detection module uses Deep Learning to perform online detection and provide the 3d pose estimations of objects present in an input image, while S-PTAM estimates the camera pose in real time. The system was tested on a real world environment, achieving good object localization results.
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.
