A review on cloud robotics based frameworks to solve simultaneous localization and mapping (slam) problem

January 29, 2017 · The Cartographer · 🏛 arXiv.org

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"Title-pattern auto-detect: A review on cloud robotics based frameworks to solve simultaneous localization and mapping (slam) pr"

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Authors Rajesh Doriya, Paresh Sao, Vinit Payal, Vibhav Anand, Pavan Chakraborty arXiv ID 1701.08444 Category cs.RO: Robotics Citations 5 Venue arXiv.org Last Checked 3 days ago

Abstract

Cloud Robotics is one of the emerging area of robotics. It has created a lot of attention due to its direct practical implications on Robotics. In Cloud Robotics, the concept of cloud computing is used to offload computational extensive jobs of the robots to the cloud. Apart from this, additional functionalities can also be offered on run to the robots on demand. Simultaneous Localization and Mapping (SLAM) is one of the computational intensive algorithm in robotics used by robots for navigation and map building in an unknown environment. Several Cloud based frameworks are proposed specifically to address the problem of SLAM, DAvinCi, Rapyuta and C2TAM are some of those framework. In this paper, we presented a detailed review of all these framework implementation for SLAM problem.