A review on cloud robotics based frameworks to solve simultaneous
localization and mapping (slam) problem
release_heunhfa7qratzj3724edmwlzgm
by
Rajesh Doriya, Paresh Sao, Vinit Payal, Vibhav Anand, Pavan
Chakraborty
2017
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.
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