Unmanned Ground Systems: A Quieter Path to Autonomy

Unmanned Ground Systems (UGS) are poised to generate a significant societal impact through 2040.  Aerial and maritime (UAS and UMS, respectively) will continue to garner headlines and make waves, but in terms of every day impact, ground systems are where the rubber will meet the road.

UAS and UMS will continue to grow and penetrate many areas of daily life.  UAS is the most popular application of unmanned systems.  As both an entertainment and commercial venture, it will continue to see large sales volume numbers.  These numbers don’t necessarily translate into impact.  UAS and UMS will excel in performing tasks that are largely invisible to everyday life.  Unmanned airliners would feel the same and do the same things as they do now.  Unmanned cargo ships and water taxis would move people and goods from point A to point B just as they do now.  The application of both these systems in the military environment would be significant in reducing risk to aviators and sailors, both critical, but not drive a major shift in how society functions.

UGS, however, opens up a key path to changing how society operates daily – driving.  If in no other metric aside from reducing man-hours behind the wheel, the second and third order societal impact of recovering those lost hours in incalculable.  Cars change everything, even in developing areas of the world where cars aren’t ubiquitous. This is because the car will be a product of a greater autonomous capability, one not limited to any particular arena (Koehler, 2017).  The technology required to make cars truly autonomous infers a capability of machines to utilize an internal OODA (observe, orient, decide, act) loop (Boyd, 1987; Shu, 2016).  Observation and action, the bookends of OODA, are the input/output mechanisms of mechanical and electrical systems of old.  Orientation and decision, on the other hand, imply a consideration of multiple data and responses that lead to the choice of action.  This is the foundation of AI and with AI comes a path to true machine autonomy, not autopilot programming.  Therefore, which unmanned technology, aerial or ground, will drive AI development faster and implement those developments sooner?  The answer to that question tells us which system will have the greatest societal impact in the next 20 years.  The UAS developers are pushing this envelope from their side through refining swarm technology.  Swarms are based on interactive behaviors among closely operating vehicles, which has carryover application to UGS.  In this manner, UAS innovation may push UGS technology to faster adoption and be a contributor to its ultimate success.  The UGS endeavor to reach human independence is, at this time, the frontrunner to changing the transportation, and ultimately societal, landscape.

The result of deep machine processing will reveal from what humans are removed.  If these results are abstracted over their applications, a broader evolutionary trend can emerge describing how humans are allowed out of the loop.  If UGS leads to autonomous cars, and autonomous cars drive AI maturation, then society will be fundamentally altered.  Beyond drone’s performance of the 3 D’s of dull, dangerous, and dirty work, unmanned, smart machines will become a partner to humanity.


Boyd, J. (1987). A Discourse on Winning and Losing. Maxwell Air Force Base, Air University Library Document, No. M-U, 43947.

Koehler, C., Appel, D. & Beck, H. (2017, January).  Winning strategies in the race for connected autonomous cars.  Auto Tech Review, Volume 6 (1). 36. doi:10.1365/s40112-017-1275-3

Shu Z., Jia Q., Li X., Wang W. (2016, September 22) An OODA Loop-Based Function Network Modeling and Simulation Evaluation Method for Combat System-of-Systems. In: Zhang L., Song X., Wu Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim 2016, SCS AutumnSim 2016. Communications in Computer and Information Science, vol 644. Singapore:  Springer



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