Abstract

The Simultaneous Localization and Mapping (SLAM) method is becoming more and more established for the localization of mobile robots in indoor environments. Due to the high complexity of SLAM, high computing resources are necessary, which leads to a shorter runtime. By using edge computing and higher bandwidths of new wireless technologies, the computing can be outsourced. In this work, the SLAM process is offloaded from a mobile robot to an edge cloud and the impact of more computing power is investigated. We show that outsourcing has performance advantages in terms of the update rate of the map generation as well as the localization.

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 call

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.