Abstract
With the rapid development of big data, cloud computing and other technologies, Cloud-based robotic has become one of the key research directions for service robot, such as used in hospitals. A framework and set of metrics for evaluating the quality of service (QOS) of a cloud robotic platform would be greatly facilitate research into and actual practice of service robots. In this paper, a QOS metrics framework of cloud robotic computing is summarized and the research of components and metrics of a cloud robotic platform is reviewed. QOS metrics are organized into software, network, and robotic services. By summarizing and analyzing the above three groups of metrics, a QOS framework or index system is proposed. Finally, future research towards open source and standardization of components of robotic cloud platform is discussed.
Highlights
In the fourth industrial revolution, robotic technology has played an important role
Maturity reflects scientific and standard degree of software and whether there are rules for management; fault tolerance reflects the ability of software detection and correction; recoverability refers to the ability to recover process and data in case of software failure; Maturity depends on rigor in the software design process, while the other two groups of metrics can be evaluated by computer simulation of major accident simulation and other operations Estimate
With the market development and application integration of public cloud and private cloud, as well as a series of policies on cloud computing industry issued by many governments, more and more intelligent services are linked with cloud services
Summary
In the fourth industrial revolution, robotic technology has played an important role. Through the above three aspects, this paper is committed to establish a QOS metrics framework of cloud robotic platform. Realization of grasping by service robot is limited by amount of data transmission, calculation speed, timeliness, etc., which cannot be carried out through the cloud platform, and is more suitable for its own terminal. The cloud platform carries a large number of data stream transmission through network, and needs to summarize a corresponding QoS metrics in network for evaluation. After summarizing and analyzing the above three methods, a scientific QOS metrics framework of cloud robotic platform is obtained, and a future direction of the framework is prospected.
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