Industry 4.0 is a collective term (created in Germany) for the technological concepts of cyber-physical systems, the Internet of Things and the Internet of Services, leading to the vision of the Smart Factory. Within a modular structured Smart Factory, cyber-physical systems monitor physical processes, and make decentralized decisions. Over the Internet of Things, cyber-physical systems communicate and cooperate with each other and humans in real time. In addition, one of the aims in robotics is to build smarter robots that can communicate, collaborate and operate more naturally and safely. Increasing a robot’s knowledge and intelligence is a vital for the successful implementation of Industry 4.0, since traditional approaches are not flexible enough to respond to the rapidly changing demands of new production processes and their growing complexity.
As identified in both academia and industry, there are several design principles in Industry 4.0, which support companies in identifying and implementing Industry 4.0 scenarios:
- Interoperability: the ability of cyber-physical systems (i.e. workpiece carriers or assembly stations) and humans to connect and communicate via the Internet of Things
- Virtualization: linking sensor data (from monitoring physical processes) with virtual plant models and simulation models
- Decentralization: the ability of cyber-physical systems within Smart Factories to make decisions on their own
- Real-Time Capability: the capability to collect and analyze data and provide the derived insights immediately
- Service Orientation: offering of services (cyber-physical systems, humans or Smart Factories)
- Modularity: flexible adaptation of Smart Factories to changing requirements by replacing or expanding individual modules
In addition, one of the aims in robotics is to build smarter robots that can communicate, collaborate and operate more naturally and safely. Increasing a robot’s knowledge and intelligence is a vital for the successful implementation of Industry 4.0, since traditional approaches are not flexible enough to respond to the rapidly changing demands of new production processes and their growing complexity. Linked data represents a promising approach to overcome limitations of the state-of the- art solutions. The following list of topics is indicative:
- Knowledge Representation for Robotics
- Data integration
- Motion and task planning
- Manipulation and grasping
- Object and place recognition
- Human-Robot and Robot-Robot Interaction
- Navigation
- Databases for robotics applications
- Multidisciplinary Topics
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