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 Multi-Modal Crew Interface Designs, which are part of the laboratory’s Human-Autonomy Teaming Essential Research Program. The project involves the development of technologies that support Soldiers’ ability to team with AI-enabled robotic tanks.
Dialogue is one of the most basic ways humans use language, and is a desirable capability for autonomous systems. Army researchers developed a novel dialogue capability to transform Soldier-robot interaction and perform joint tasks at operational speeds. The fluid communication achieved by dialogue will reduce training overhead in controlling autonomous systems and improve Soldier-agent teaming.
Researchers from the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory, in collaboration with the University of Southern California’s Institute for Creative Technologies, developed the Joint Understanding and Dialogue Interface, or JUDI, capability, which enables bi-directional conversational interactions between Soldiers and autonomous systems.
The U.S. Army Combat Capabilities Development Command’s Army Research Laboratory designated several research programs as essential for future Soldier capabilities. Of these major flagship programs, the Human Autonomy Teaming, or HAT, Essential Research Program focuses on the relationship between humans and AI and how to establish human-robot teams that can survive and function in complex environments.
According to the researchers, AI and machine learning technologies enable the processing of large volumes of data very rapidly, which allows warfighters to make decisions faster and with greater confidence. This increase in processing capability will also accelerate the pace of actions on the battlefield and result in the emergence of even more complex situations to consider.
As the U.S. Army revamps its small arms training and raises rifle qualification standards, researchers are studying alternative training and tools to help improve Soldier performance.
he U.S. Army Combat Capabilities Development Command’s Army Rese