Robots have been widely adopted to perform critical tasks in various fields in the past several years. Due to the limitations of its local resources, the capability of a single robot is usually severely restricted. Cloud robotics has been recently proposed to extend the capability of robots by leveraging the rich services provided in cloud. However, robotic applications generally give considerable attention to quality of service (QoS) because these applications interact directly with the physical world. Fulfilling strict QoS requirements while utilizing cloud services, the performance of which is highly unpredictable, is a great challenge. In this paper, we propose a novel hybrid architecture for cloud robotics, named RoboCloud, to address this challenge. Instead of simply integrating robots with public cloud services, RoboCloud introduces a task-specified mission cloud with controllable resources, predictable behavior. The mission cloud can extend the capability of the robot on its specified, predictable tasks without sacrificing QoS. For general tasks beyond the capability of the mission cloud, we opt for public clouds, i.e., various cloud services available on the Internet. We successfully apply this architecture to realize robotic object recognition, which is a fundamental capability of autonomous robots who interact with an open environment. We can minimize the recognition latency of objects that are predicted to appear in a specific task without sacrificing the capability to recognize unfamiliar, unexpected objects by seamlessly integrating a specialized mission cloud, a public object recognition service on the Internet.
['Yiying Li', 'Huaimin Wang', 'Bo Ding', 'Peichang Shi', 'Xuan Liu']
Toward QoS-Aware Cloud Robotic Applications: A Hybrid Architecture and Its Implementation