By Archana Pyati
In November 2025, the Department of Defense announced that it would focus on six critical technology areas that will “define the future of American military superiority.” The six areas represent “the cutting edge of research and engineering” aimed at ensuring that the United States military “remains the most lethal fighting force in the world.” Underpinning these six technology areas are decades of basic science and fundamental research conducted at America’s research universities.
In a series of articles, AAU is highlighting the contributions of university research in developing critical technology areas. This article – the third of six – discusses the federally funded, university-based research behind technologies that allow the military to continuously operate in contested logistics environments in which supply chains are under active threat by adversaries or inaccessible due to geopolitical instability or unforgiving geography, terrain, or weather.
As long as societies have waged war, logistics have been central to successful military campaigns. Logistics – the ability to store, manage, and transport artillery, fuel, food, equipment, and medical supplies to warfighters when they need them – are often what makes the difference between victory and defeat.
“Infantry wins battles, logistics wins wars,” observed U.S. Army General John J. Pershing, who successfully led the American Expeditionary Forces during World War I.
But what happens when the supply chain itself is under attack or cannot be accessed – before the fighting has even begun or troops have had the chance to resupply?
The U.S. military is increasingly planning for “contested logistics” environments, in which adversaries seek to “deny, disrupt, destroy, or defeat” operations at every node in the supply chain, according to U.S. Army supply chain expert Maj. Jon Michael King. Sometimes, it isn’t merely hostile actors that must be thwarted, but the “tyranny of distance,” as in the Indo-Pacific theater where logistics are conducted over 100 million square miles covering islands, archipelagos, volcanos, and vast expanses of open water.
Contested logistics – "when the supply chain is the battle" – is now the default scenario for military planners. This encompasses both disruptions to physical infrastructure – roads, bridges, ports, sea lanes, or airspace – and cyberattacks that compromise communications networks and data that are essential for deploying arms and supplies to front lines.
The military relies on emerging technologies to protect and manage global supply chains in contested environments. These include predictive analytics and logistics, autonomous or unmanned systems, additive manufacturing, and microgrids that deliver localized power. These technologies incorporate advances in artificial intelligence (AI), machine learning, engineering, materials science, synthetic biology, and distributed energy, which themselves grew out of breakthroughs in computer science, cognitive science, mathematics, physics, chemistry, and life sciences carried out by university scientists and researchers.
Since World War II, universities have been steady partners with the U.S. military in advancing innovation for secure and efficient (and now intelligent) supply chains. Universities have done this through both the curiosity-driven scientific research behind the innovation and in subsequent testing and development of new technologies.
Predictive Analytics: The Brains
Predictive analytics and logistics have become indispensable to military sustainment professionals who must proactively plan for the unexpected.
Similar to commercial enterprises that manage global supply chains and inventory, the military uses predictive analytics to forecast demand with precision and direct materiel or services (such as vehicle repair or maintenance) to the right place at the right time. Predictive analytics rely on vast troves of real-time data and intelligence gathered from drones, sensors, and satellite imagery as well as historical data from the physical environment or past combat operations.
AI models are trained on these data, employing machine learning to detect patterns of resource usage in contested environments and recommend actions for decision-makers without being explicitly programmed to do so. The result is an optimized supply chain that reduces costs and lag between when warfighters request support and when support gets to them.
AI and machine learning are fundamental elements of predictive analytics, developed from research that kicked off in the 1960s and made huge leaps in the 1970s and 1980s through algorithms and neural networks developed by Geoffrey Hinton, John Hopfield, David E. Rumelhart, and other AI pioneers – many of whom were affiliated with AAU member universities (such as Princeton University, Stanford University, and the University of California San Diego). Predictive software for military, civilian, and humanitarian supply chains continue to be active areas of research and innovation on AAU campuses, with the Massachusetts Institute of Technology’s Center for Transportation and Logistics being a prime example.
Autonomous Systems: The Brawn
As we have seen in the Ukraine-Russia conflict and Iran’s response to Operation Epic Fury, unmanned drones are now an inexpensive-yet-lethal staple of modern warfare. But drones, robots, and other autonomous vehicles can also limit loss of life by transporting supplies without human operators being physically present and in the line of fire.
If predictive analytics are the “brains” of contested logistics, enabling military planners to accurately forecast and manage the movement of goods, then autonomous systems are the “brawn," the physical means of replenishing warfighters. To be sure, autonomous systems aren’t all muscle: embedded AI sensor technology makes it possible for them to perceive and navigate their surroundings, remotely supervised by military personnel.
Autonomous systems bring AI “out of the digital realm and into the physical world to perform complex tasks,” according to the World Economic Forum. Like predictive logistics, autonomous systems are rooted in artificial neural networks and machine learning algorithms developed by university scientists. These systems also evolved out of decades of federally funded university research in robotics, engineering, and more sophisticated forms of machine learning ( reinforcement learning and imitation learning ).
Early experiments in intelligent robotics began in university research labs. Shakey, the first AI-powered robot, debuted in the early 1970s after years of work by Charles Rosen and other researchers at the Stanford Research Institute (now SRI International) supported by the Defense Applied Research Projects Agency (DARPA). DARPA also funded the research of Robert McGhee and Ken Waldron, the Ohio State University engineers who built Walker – a six-legged mechanical walking machine designed to carry cargo over rough terrain. In the early 2000s, DARPA devoted its Grand Challenge and Urban Challenge programs to autonomous vehicle research and prototyping. And the National Science Foundation (NSF) has made decades-long investments in university robotics research.
For robots operating under contested logistics, SLAM (simultaneous localization and mapping) is a game-changing technology. Developed by researchers in the 1980s and 1990s, SLAM enables robots to navigate environments without the assistance of global positioning systems (GPS). Robots use SLAM to sense their position and build their own mental maps – absolutely essential for moving through contested territory or airspace. John J. Leonard, an MIT mechanical engineer supported by the Office of Naval Research and DARPA, developed the early SLAM algorithms. He worked alongside the University of Pennsylvania-educated British-Australian researcher Hugh Durrant-Whyte and other robotics researchers.
Additive Manufacturing for a “Just in Time” Strategy
What about situations when military logisticians simply cannot get supplies to the front line on time? The military is planning scenarios for which spare parts or medical supplies need to be produced in real time and on site.
Advancements in 3D printing and other additive manufacturing technology as well as next-generation materials have made it possible for forward-deployed troops to fabricate materiel when they need it. This type of decentralized field manufacturing has the potential to save the military time and money by speeding up the supply chain. Logistics professionals consider this a more efficient “just in time” strategy compared to a “just in case” approach that relies on large stockpiles of inventory that may or may not be utilized.
Additive manufacturing uses printers to create three-dimensional objects one layer at a time (hence the name “additive”), based on a digital blueprint or design. The field has advanced over decades through breakthroughs from both industry and university-based engineers, dating back to the invention of stereolithography, a technique patented in 1986 by entrepreneur Charles Hull that fuses together layers of liquid resin in large vats to create plastics and other material.
A few years later, MIT engineering researcher Emanuel Sachs developed binder jetting, a technique that mimicked ink jet printers by layering powder and liquid binders to create solid objects. Binder jetting became what we now understand as 3D printing. Sachs’ research received significant support from NSF, which had been funding the precursors to additive manufacturing, including computer-aided design, since the 1950s.
Microgrids and Distributed Energy for Consistent Access to Power
The U.S. military is the among the world’s largest institutional consumers of electricity. In contested environments, access to electric power is likely to be unreliable. Overseas military bases are dependent on centralized grids and long-distance transmission lines of a host city or nation. Natural disasters, cyberattacks, or hostile actors may deny or disrupt access to centralized energy infrastructure, leaving troops without reliable sources of power.
The military is therefore increasingly turning to distributed energy – energy generation and storage across multiple access points – to create resilient energy supply chains. Microgrids are self-sufficient localized energy systems that store and generate their own power from renewable, biomass, or conventional energy sources and can be either connected to centralized grids or function autonomously. Microgrids have a central controller or “brain” that analyzes data on energy usage and availability and can switch into “island mode” when disconnected from the larger grid, drawing on power stored in batteries.
Microgrids are made possible by advancements in solar, wind, and geothermal energy science, which led to the development of photovoltaic technology (solar panels), turbines, and other specialized infrastructure. Battery storage technologies grew out of basic chemistry and materials science research devoted to engineering novel chemicals and materials to facilitate the storage and flow of electricity. University researchers have pioneered battery technology – notably John B. Goodenough (University of Texas, Austin), M. Stanley Whittingham (SUNY Binghamton) and Akira Yoshino (Meijo University, Japan), recipients of the 2019 Nobel Prize in chemistry for inventing the lithium-ion battery. AAU member campuses are actively engaged in distributed energy research and development, including the Georgia Institute of Technology, Texas A&M University, and UC San Diego.
Contested Logistics as the Default Setting for Sustainment
Military planners increasingly assume a contested logistics environment for future conflicts in which supply chain sustainment is under constant threat and exposed to all manner of risks. Universities will continue to serve as partners with the military in both fundamental research and technology development to create secure, resilient, and responsive supply chains. That way warfighters can keep their focus on the battlefield without concerns about whether the next round of munitions, fuel, food, and medicine will arrive on time.
Archana Pyati is editorial and content officer at AAU.