Human-Machine Interaction: Collaborative Robotics

Type of course:

Digital learning, Path

Language:

Duration:

2 hours

Workload:

4 hours

Proficiency:

Intermediate

Target:

Professionals, Manager, Workers

In a mass customized production, an upcoming Industry 5.0 concept starts to introduce innovative ways of organizing Human-Centric production systems that allow enhancing flexibility, and effective task distribution between robotic agents and human laborers, enabling a high level of predictiveness considering individual aspects of a human worker.

The upcoming educational materials learning path offers comprehensive nuggets that focus on collaborative production systems, IoT (Internet of Things), wearables, digital twins, virtual commissioning, and human-machine interfaces. This learning path is designed for individuals interested in gaining expertise in these emerging fields and staying up-to-date with the latest advancements and practicalities.

At the end of the Learning Path, the users can:

– Cite the relevant robotization use cases in manufacturing;
– Define the limitations of the use of collaborative robots in industry and design suitable applications;
– Explain the relevant practicalities of cobots and AGVs (Autonomous Guided Vehicles);
– Conclude what are the most relevant scenarios where using Robotics may benefit a business.

Learning outcomes

After completing the learning module, the user can design and develop a Digital Twin of collaborative production units that include collaborative robots and human operator.
After completing the learning module, the user can create a human factors data flow using Message Queuing Telemetry Transport (MQTT) and Open Platform Communications Unified Architecture (OPCUA).
After completing the learning module, the user can define the limitations of the use of collaborative robots and Autonomous Guided Vehicles (AGVs) in industry, analyze the state of production, design suitable application and conclude, what are the most relevant scenarios, where using Robotics may benefit a business.