Co-production CeLL performing Human-Robot Collaborative AssEmbly


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 a 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 CoLLaboratE project will build upon state-of-the-art methods for teaching the robot assembly tasks using human demonstration, extending them to facilitate genuine human-robot collaboration. To this end, a framework for equipping the robots and AGV mobile platforms with basic collaboration skills, such as load sharing, human touch recognition and human intention detection, will also be developed, coupled with deep reinforcement learning algorithms for increasing adaptability. Special attention will be paid to providing effective safety strategies allowing the use of a fenceless approach within the production cell.

As a result, closer collaboration will be achievable and efficient production plans making optimal use of the available resources will be designed and executed. The proposed solution will be evaluated in four different pilot sites, which will be implemented as collaborative factory floors of the industrial partners in Italy, Slovenia, Turkey, and Romania.

More information
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Start date: 01-10-2018
End date: 30-09-2021
Total budget - Public funding: 6 864 600,00 Euro - 6 864 600,00 Euro
Call topic: Effective Industrial Human-Robot Collaboration (RIA) (DT-FOF-02-2018)
Twitter: @collaborate_eu
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    In order for CoLLaboratE to successfully realize its vision several prerequisites are set in the form of major Scientific and Technological Objectives throughout the project duration. These are summarized in the following points:

    Objective 1: To equip the robotic agents with basic collaboration skills easily adaptable to specific tasks

    Objective 2: To develop a framework that enables non-experts teaching human-robot collaborative tasks from demonstration

    Objective 3: The development of technologies that will enable autonomous assembly policy learning and policy improvement

    Objective 4: To develop advanced safety strategies allowing effective human robot cooperation with no barriers and ergonomic performance monitoring

    Objective 5: To develop techniques for controlling the production line while making optimal use of the resources by generating efficient production plans, employing reconfigurable hardware design, and utilising AGV’s with increased autonomy

    Objective 6: To investigate the impact of Human-Robot Collaboration to the workers’ job satisfaction, as well as test easily applicable interventions in order to increase trust, satisfaction and performance

    Objective 7: To validate CoLLaboratE system’s ability to facilitate genuine collaboration between robots and humans


    The CoLLaboratE project will have profound impact on strengthening the competitiveness and growth of companies in the manufacturing sector:

     - CoLLaboratE will develop a co-production cell for manufacturing production lines, capable to perform assembly operations through human-robot collaboration. This cell will be the result of inter-disciplinary technological advances that will be realized during the project, in a series of highly significant areas related to robotics and artificial intelligence. By the end of the project, the proposed system will be demonstrated and evaluated at TRL6, being ready for commercial take-up, allowing this assembled knowledge to be in turn, rapidly integrated in real production lines of industries and SMEs.

    - CoLLaboratE will develop technologies for autonomous and collaborative assembly learning and teaching methods by non-experts so that no explicit robot programming will be required. As the products of industries, such as LCD TV’s rapidly evolve, flexibility so as to easily adapt in a new assembly task regarding a new product, is a major quality sought for modern assembly lines. Robots that need several months to be programmed and start working on the task are a rather unrealistic solution. Given the (a) time-consuming programming process typically required for industrial robots and (b) difficulties posed to robots from uncertainties in small parts assembly, cheap labour hands of low cost countries (LCCs) have so far been typically utilized instead of robotic solutions, through LCC assembly outsourcing strategies.

    - CoLLaboratE service portfolio will include a set of innovative fast and flexible manufacturing techniques, combining the benefits of the reconfigurable hardware design and modern ICT technologies (e.g. AΙ, learning toolkit, digitization of assembling processes)

    - CoLLaboratE will introduce novel AGVs on shop floors with enhanced capabilities, that apart from motion planning and obstacle detection, they will also be capable of detecting the intentions of human users in the factory in order to provide flexibility and facilitate the production process, along with optimal use of resources.

    - CoLLaboratE will reduce delivery times and costs, whereas robot assembly techniques will also allow a much greater degree of customization and product variability. As it is highlighted in the euRobotics AISBL Strategic Research Agenda, the use of robotics in production is a key factor in making manufacturing within Europe economically viable; locating manufacturing in Europe through robotic solutions that will suppress LCC outsourcing is a major goal for the near future. Through flexible assembly lines, the manufacturing companies will be offered with great leverage over their innovation capacity and integration of new knowledge into their products.

    - CoLLaboratE will pave the way for a new era in industrial assembly lines, where robots will present genuine collaboration with the human workers and will allow manufacturing industries to establish in-house robotic-based assembly lines, capable to rapidly adapt in continuously evolving products. Through its advances, SMEs holding robotic-based assembly lines, will benefit by acting as subcontractors for large industries, since they will be a viable alternative to LCC outsourcing.

    It becomes clear that the CoLLaboratE project has profound potential to strengthen the competitiveness and growth of companies and bring back production to Europe, by implementing novel artificial intelligence technologies and integrating robots with collaborative skills in the production, meeting a specific, highly important need of European, as well as worldwide manufacturing industries toward their future growth and sustainability.


    The target users for the CoLLaboratE system are manufacturing industries in need of flexible and affordable automation systems to boost their global competitiveness. Successful completion of CoLLaboratE will allow SMEs and large manufacturing companies in Europe to easily program assembly tasks and flexibly adapt to changes in the production pipeline. Such ease of use and rapid integration time of robotic assembly systems is expected to pave the way for step change in the adoption of not only collaborative robots, but a complete collaborative environment provided by the CoLLaboratE solution.


      Expected impact: Demonstrating the potential to bring back production to Europe

      Improvement of productivity in different assembly tasks:

      i.Performing Car Starter Assembly

      ii.Windshield visual quality check and preassembly

      iii.Performing LCD TV Assembly

      iv.Αircraft parts assembly


      Expected impact of 20% reduction in production reconfiguration time and cost