This special issue presents an important research topic in robotics, focusing on the development and applications of the cloud robotics technologies in intelligent manufacturing. As robots are more widely used in industry and undertake more complex tasks, intelligent robots with stronger learning ability and environment adaptiveness is required for intelligent manufacturing. Cloud robotics is considered as a promising technology concept, where robots and automation systems share data and code and perform computation via networks building on emerging research in Cloud Computing, Deep Learning, Big Data, Internet of Things, and open-source software. With the use of cloud, the robot system is no longer limited by the local device but has a powerful real-time remote processing capacity. It can autonomously learn new skills from the cloud for different task, so as to truly achieve intelligence in manufacturing. Therefore, it is important to keep track of the fast growth of theories and technologies in cloud robotics and automation for intelligent manufacturing This special issue aims to concentrate on developments of cloud robotics technologies and their industrial applications. It will address their fundamental problems involved, either from a research perspective or an application perspective. Hence, colleagues from both academia and industry are welcome to submit papers for this Special Issue. We are encouraging cutting-edge developments, concepts and practices in cloud robotics and their industrial applications. We welcome high-quality original research with latest conceptual, theoretical, methodological or empirical contributions that will enable a better understanding in this area.
Potential topics include, but are not limited to: Cloud-Enabled robot system design, modeling and control; Cloud-based swarm control for industrial robots; Cloud-based motion planning for industrial robots; Cloud-based human-robot cooperation in intelligent manufacturing; Cloud-based sensor fusion and perception in intelligent manufacturing; Cloud robotic skill learning and task representing; Cloud robots for automated assembly; Cloud robots for automated transportation; Cognition and recognition in cloud robotics; Evaluation theories and techniques of cloud robotics in industry; Industrial applications of cloud robotic system.