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.
翻译:云体机器人是一个新兴的机器人领域,它因其对机器人的直接实际影响而引起许多关注。在云体机器人中,云计算的概念被用来向云体卸载大量机器人的计算工作。除此之外,还可以根据需要向机器人提供其他功能。同时定位和绘图(SLAM)是机器人在未知环境中用于导航和地图建造的机器人的计算密集算法之一。提出了若干基于云体的框架,专门解决SLAM、DavinCi、Rapyuta和C2TAM等问题。在本文中,我们详细审查了所有这些框架在SLAM问题上的执行情况。