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LIDARI 2017 : 2nd Workshop on Linked Data in Robotics and Industry 4.0

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Link: https://2017.semantics.cc/satellite-events/lidari-2nd-workshop-linked-data-robotics-and-industry-40
 
When Sep 11, 2017 - Sep 11, 2017
Where Amsterdam
Submission Deadline Jul 3, 2017
Notification Due Aug 7, 2017
Final Version Due Aug 28, 2017
Categories    robotics   industry 4.0   semantic   linked data
 

Call For Papers

LIDARI - 2nd Workshop on Linked Data in Robotics and Industry 4.0
Co-located with SEMANTiCS 2017 - The Linked Data Conference
https://2017.semantics.cc/

The annual SEMANTiCS conference is the meeting place for professionals who make semantic computing work, who understand its benefits and encounter its limitations. Every year, SEMANTiCS attracts information managers, IT-architects, software engineers and researchers from organizations ranging from SMEs, through non-profit organizations, public administrations to the largest companies in the world. Attendees learn from industry experts and top researchers about emerging trends and topics in the fields of semantic software, enterprise data, linked data & open data strategies, methodologies in knowledge modelling and text & data analytics.
The overall goal of the LIDARI workshop is to identify challenges and limitations in Robotics and Industry 4.0 and discuss with experts from the linked data community how linked data can be effectively applied addressing the synergies and solution approaches. 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. 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, but other topics are also welcome:
• 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

Workshop Organizers
Thomas Moser, St. Pölten University of Applied Sciences (thomas.moser@fhstp.ac.at)
Munir Merdan, Practical Robotics Institute Austria (merdan@pria.at)

Submission via Easychair using https://easychair.org/conferences/?conf=lidari2017

Related Resources

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ICITM--IEEE, EI and Scopus 2019   IEEE--2019 8th International Conference on Industrial Technology and Management (ICITM 2019)--EI Compendex and Scopus
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