Robotics Training and Competition as Novel Validation for the RxS Rating

The Navy is considering a transition of today’s platform-specific Unmanned Systems (UxS) roles for enlisted sailors to a comprehensive Robotics Systems (RxS) rating focused on the “head” of increasingly sophisticated autonomous systems. Carnegie Mellon researchers and educators have identified a combination of educational initiatives that can be adapted to meet the Navy’s needs.

However, AI technologies are now entering a period of exceptionally rapid growth, so platforms in service are likely to change frequently. Similarly, DOD policies for the responsible use of AI are still being refined, and with them the distribution of duties across personnel. Effective RxS training may therefore be most defined by the ability to learn new systems rapidly, and the training program evaluation process must prioritize tolerance of frequent KSA updates.

Our project therefore simultaneously develops an RxS training program prototype based on industry robotics technician and AI user curricula, and a reuable evaluation method for such programs based on annually updated Robotics Competitions. With each competition, updates to the KSAs and technologies may be incorporated. Further, the competition focuses on the capacity to learn new systems quickly, and so uses a novel robotic platform each year not included in any of the training programs. This method equates teams or cohorts with the methods used to train them, and so can be used to test training design hypotheses as well as compare wholly different approaches within the same competition.

Figure 1. Our approach uses two existing CMU technician curricula as a starting point. 1) SMART Robotics Technician Training (Mechanics, Electronics, Fabrication, Software, Integration), 2) SAIL() ML/AI Training (Technician-level ML/AI, AI Users/Operators modules)

RESEARCH CHALLENGES AND OPPORTUNITIES:

• How similar or dissimilar are Naval Robotics KSAs from industry needs?
• What are the transferable, foundational elements of knowledge about AI that are most valuable to RxS sailors?
• What logistical challenges must be overcome to ensure that the competition results reflect valid comparisons between training programs?
• Can robotics competitions of this type also be engaging to non-enlisted participants, creating an avenue for recruiter engagement?
• Can an autonomy/AI-centered challenge of this kind serve as a beacon for K-12 robotics competitions to update their offerings to include more up-to-date AI challenges?

This material is based upon work supported by the Office of Naval Research under Contract Number N00014-23-C-2015. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Office of Naval Research.