A Look At Our Vision

Traditional manufacturing systems lack the necessary flexibility and reconfigurability that can allow short production cycles and fast deployment of the updated system. Although the use of automation technologies based on industrial robots can increase the adaptability of a production line, the desired flexibility cannot be achieved until abilities for genuine collaboration of the robots with the human workers are developed. CoLLaboratE will revolutionize the way industrial robots learn to cooperate with human workers for performing new manufacturing tasks, with special focus on the challenging area of assembly operations. The envisioned system for collaborative assembly will be capable of allocating human and robotic resources for executing the production plan sharing the tasks according to the capabilities of the available actors. The planned extensions that will lead to the CoLLaboratE solution are analysed below:

Key Collaboration Skills

  • Adaptive robot control in collaborative tasks with physically coupled actors
  • Collaborative behaviour primitives
  • Human Touch Recognition and Classification
  • Detection of Human Intentions for AGVs and Professional Gesture Recognition

Smart Learning of Collaborative Assembly Tasks

  • Learning from human demonstration (visual and/or kinaesthetic)
  • Autonomous Assembly Policy Learning and Policy Improvement
  • Multimodal Learning of Assembly Tasks

Human Monitoring and Safety

  • Dynamic active constraints construction and enforcements for human safety during HRC
  • Monitoring the Ergonomic Performance of the Operator

Human-Robot Collaboration Planning System and Reconfigurability

  • Efficient Production Planning Optimising the Utilisation of Human and Robotic Resources
  • Fast Adaptation of Co-Production Cell through Reconfigurable Hardware Design

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 820767.

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Project Coordinator
Prof. Zoe Doulgeri
Automation & Robotics Lab
Aristotle University of Thessaloniki
Department of Electrical & Computer Engineering
Thessaloniki 54124, Greece
Collaborate Project CoLLaboratE Project
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