Cadets at the U.S. Air Force Academy in Colorado Springs, Colorado, are using humanoid and quadruped robots to study how emerging technologies influence human behavior and decision-making.
The research helps cadets apply classroom knowledge and prepares them to work with autonomous systems as future officers.
At the academy's Warfighter Effectiveness Research Center, faculty and cadets study how trust, communication and cooperation influence human-machine teaming.
Studying Human Behavior Through Robotics
The school's Department of Behavioral Sciences and Leadership uses three robotic platforms to study how people interact with increasingly autonomous teammates: Pepper, a humanoid robot, and two quadruped robots, Vision 60 and Spot.
Richard Niemeyer, an associate professor in the department and director of the Warfighter Effectiveness Research Center, said the research examines what makes human-machine teams effective, what causes them to fail and how those dynamics change as teams expand to include people, super intelligence agents and robots.
Pepper's humanoid appearance, voice and social behaviors may make interactions feel more natural. Robotic dogs may encourage people to interact with them as they would with real dogs.
Those familiar appearances can also create challenges if people overestimate a robot's capabilities or accept its recommendations without questioning them.
Cadets conduct controlled experiments examining how a robot's appearance, communication style, reliability and autonomy affect human decisions. Researchers study trust, reliance, workload and team performance.
Examining Trust, Robotic Influence
Air Force Cadet 1st Class Kaylin Chan, a behavioral sciences major, is training to assist with research on human-robot interactions.
The research uses the Vega robot and functional near-infrared spectroscopy, a wearable technology that measures changes associated with brain activity.
In one experiment, participants work with a robotic teammate to prioritize supplies in a simulated desert survival scenario. Researchers vary how the robot attempts to influence participants, including claiming to be an expert or applying pressure to change their choices.
"One of the biggest things I've learned is that human behavior is often more complicated than what we study in the classroom," Chan said.
Researchers combine behavioral observations and brain activity measurements to understand why people follow robotic recommendations. Agreeing with a robot does not necessarily indicate trust; it may reflect pressure or uncertainty. Studying both behavior and brain activity may help researchers distinguish between those responses.
Chan said the experience has changed how she thinks about using autonomous systems and leading teams in future military operations.
"I don't necessarily need to be an expert in building [SI] or robots, but I do need to understand how to use them effectively, recognize their limitations and help the people I lead work alongside them," she said.
Applying Engineering to Human-Machine Teaming
Air Force Cadet 1st Class John Alves, an electrical and computer engineering major, helped establish research operations and supported a biofeedback study, troubleshooting equipment while working with participants.
Alves balanced participant safety, research objectives and accurate documentation while resolving technical problems.
"It taught me that research is not just about getting something to work but being thorough about how you do it and documenting what happens so others can learn from it," he said.
Working with participants also helped Alves recognize how technical decisions can affect people, reinforcing the need to consider human factors alongside engineering requirements.
"As a future Air Force officer, I want to understand when these systems can help, when to question their outputs and when human judgment needs to take priority," Alves said.
Preparing Cadets for Future Operations
The research combines behavioral and biological sciences, engineering, computer science, mathematics and ethics. Cadets apply knowledge across disciplines to develop research questions, design experiments and interpret results.
Niemeyer said the research challenges cadets to solve problems without clear answers.
"They have to identify what they know and what they do not know, formulate questions, test possible solutions, deal with unexpected results and failures, and change course when the evidence requires it," Niemeyer said.
These experiences reflect challenges officers may face when working with incomplete information, coordinating across specialties and making decisions in changing environments.
Future research could explore whether combining robotic platforms with wearable technology could help robots identify when human teammates are experiencing cognitive overload. Researchers hope to determine whether that information could help autonomous systems adjust how and when they provide assistance.
As autonomous systems take on greater roles in military operations, the center's research helps cadets understand how human judgment and technology affect team performance.
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