Real time dynamic motion planning applied to Agile production

Real time dynamic motion planning applied to Agile production

The DynaMo project aims to apply the RTDMP bin picking mechanism in agile manufacturing hence, increasing flexibility, adaptability and agility in robotic picking systems.

The solution

DynaMo is a joint effort of leading experts in production, industrial automation and dynamic motion planning (DMP) technologies towards a smooth and wider adoption of collision-free adaptive motion planning solutions that allows robots to perform safely in dynamic, unstructured, and collaborative workspaces, while instantaneously reacting to changes as they occur and ower barriers for manufacturers to make advances in agile production.


Challenge

Human-robot collaboration combine the advantages of robots (accuracy, speed and repeatability) with the flexibility and cognitive skills of human workers. They represent a natural evolution that can solve existing challenges in manufacturing and assembly tasks that are too complex to program for robots to do alone. For small- and medium-sized enterprises they will serve the needs for reduced lead times and flexible multipurpose assembly systems.



Impact

The impact of the technology
will be measured within the project:
1) How much time (lines of computer code) can be saved with RTDMP
when setting up new tasks
2) How much can cycle times be reduced because of more optimal paths for
the robot with RTDMP
3) How many cases RTDMP becomes necessary to “empty” the entire bin of objects
to pick.

Facts and figures

  • FSTP Name:

    DynaMo

  • Beneficiary Lead:

    Adaptive Robotics AS

  • Beneficiary 2:

    -
  • Beneficiary 3:

    -
  • Technology Area:

    IoT

  • End User:

    For small-and medium-sized enterprises they will serve the needs for reduced lead times and flexiblemultipurpose assembly systems.

  • Start Date - End Date:

    01/07/2020 - 30/09/2021

  • Duration:

    15 months

  • FSTP Funding:

    183 750,00 €

  • TRL Level at Start:

    -

  • TRL Level at End:

    -

  • Number of early adopters raised:

    -

  • Project results
    back to success stories
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