Related News from around DEVCOM ARL
For most tools, the outcome of its usage depends almost entirely on the actions of its human wielder. Due to the rise of automation and artificial intelligence, the growing prevalence of smart technology has complicated the once simple relationship between person and machine. In order to navigate this new and unexplored landscape of human-machine interactions, the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory named the study of human-autonomy teaming as one of its top research priorities.
Army researchers developed a novel computational model for gathering cognitive data that may be a game changer in the fields of neuroscience and econometrics, and has broad relevance to networked and multi-agent systems.
At the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory and the University of Maryland, College Park, researchers developed what is known as the Autoregressive Linear Mixture, or ALM, a novel model for analyzing time-series data, or how things change over time.
Future technology may be able to monitor and modify the brain to produce enhanced team performance, while increasing the efficiency and accuracy of decisions. The U.S. Army Combat Capabilities Development Command’s Army Research Laboratory, the Italian Institute of Technology, Italy, Harvard Medical Schooland the University of California, Irvine teamed up to study and advance research on the complexities of the human brain. Scientific Reports recently published the discoveries from their study.
Army researchers recently completed a simulation study where crew members and artificial intelligent agents demonstrated trust and cohesion while working together.
U.S. Army Combat Capabilities Development Command’s Army Research Laboratory researchers and U.S. Army Military Academy cadets conducted the study as part of an academic capstone project. It also supports the Army Wingman Joint Capabilities Technology Demonstration and the Army’s Next Generation Combat Vehicle mission prioritization.
Something is different, and you can’t quite put your finger on it, but your robot can. Even small changes in your surroundings could indicate danger. Imagine a robot could detect those changes, and a warning could immediately alert you through a display in your eyeglasses. That is what U.S. Army scientists are developing with sensors, robots, real-time change detection and augmented reality wearables.
Army researchers demonstrated in a real-world environment the first human-robot team in which the robot detects physical changes in 3D and shares that information with a human in real-time through augmented reality, who is then able to evaluate the information received and decide follow-on action.
Human facial expressions could be one of the keys in building trust between Soldiers and autonomous agents. In typical studies, researchers define groups of people, and either specify and examine variables within those groups or apply variables as measures that tend to represent entire population samples by simple group tendencies. In these traditional constructs, researchers treat sample variability within the experimenter-specified groups as noise. The Army researchers proposed a new approach, using flexible mixture modeling, which inferred and sorted individuals into four sub-groups by observed differences in traits (e.g., age, personality and maladaptive coping strategies associated with uncertainty) and states (e.g., initial trust, stress and workload perceptions).
Artificial Intelligence, or AI-enabled systems are a part of everyday life -- people use AI software to figure out the best way to navigate to new places, ask virtual agents in phones to answer questions, as well as have robots patrol the supermarket to ensure shelves stay stocked. The military is no exception -- it expects robots to do dull, dirty dangerous jobs. AI support tools help solve complicated problems.
At the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory, researchers developed Transparent Mul