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Robotics Digital Twin Initiative

Robotics Digital Twin Graphic (Physical and digital mockup of a robotic claw)

The Massachusetts Robotic Digital Twin Initiative seeks to provide capital grant funding to proposals for innovative robotic designs and applications and will support both the building of the robot and the creation of its digital twin, which will be publicly available for use by other researchers or entrepreneurs.

Program Goals

Robotic Digital Twins are advanced simulations that replicate a robot’s ability to sense and move in its environment. Experimentation on physical robots can be costly and potentially dangerous, especially when the experimentation can be unpredictable. Some examples include: 

  1. Educational spaces where students should feel comfortable making mistakes;
  2. AI research involving potentially unpredictable algorithms as well as learning from failure; and
  3. Automating existing processes, including required testing of multiple robotic systems to find the best fit. 

Digital twins enable users to work with robots in a zero-risk environment because they are both low-cost and unbreakable.

There are significant barriers to using digital twins due to the need to build them from scratch or invest in integration services. Many of the users who would benefit most from robotic digital twins do not have the knowledge or capacity to develop them themselves. This in turn limits access to experiential robotics training, physical AI research and robot adoption for logistics and manufacturing purposes.

Eligibility

Applicants must be a Massachusetts-based nonprofit, university research lab, or small-to-midsized business whose primary focus is research or development of a novel, hardware-based robotic platform. To be considered, applicants must demonstrate the technical ability to develop a digital twin of their product and affirm that MassTech can make this digital twin of their product publicly available.

Applicants must also present a strong business case for productizing or manufacturing their robotic platform.

Application Deadline is Friday, January 9

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