Abstract
This poster paper will discuss a variety of items related to Human-Machine Teaming and research in support in-creasing control of autonomous machines present in phys-ical problem domains of interest. Many military tasks can be decomposed into their primary elements – intelligence preparation, reconnaissance, movement, maneuver, fires, and and support across the combat domains of interest – air, land, sea, etc. There are an increasing number of au-tonomous and semi-autonomous ground-based systems available, such as the Multi-Utility Tactical Transport (MUTT) Unmanned Ground Vehicle, for movement of materials, or Quadrupedal Unmanned Ground Vehicle (QUGV) for the disposal of explosive ordinance, comple-mented by aerial platforms considering of a wide variety of Unmanned Aerial Systems (UAS) for the gathering and transmitting of information, held together by a common backbone and network. The preponderance of new systems and capabilities brings new issues, one of which is critical to research - how to control and manage a large number of systems. Commercial systems of significantly less capability, such as light-up drone shows, involve approximately 2 people per 100 drones; meaning that a single controller for a sin-gle drone is simply a non-starter. How can research be applied to scale the complexity of operations upwards without additional demands of personnel? This poster discusses several portions of early-stage research into a variety of applications, including: Reasoning about mixed-team processes, includ-ing real/synthetic teammates, and how infor-mation gathered about the use of synthetic teammates within simulation can be transitioned into utilization for a robotic teammate Embedding affective information into dialogue channels in order to save cognitive bandwidth Repurposing of foundational dialogue models for specific tasks and purposes Utilizing psychological research to design sys-tems in order to infer user intent Theory of mind research for autonomous systems regarding their human operators Simulated environments and agents in order to test the simulations in representative areas. Common-Sense reasoning augmented by Large Language Model technology for instructing ro-botic platforms The following things will be discussed at the poster ses-sion, representing a portfolio of ongoing work addressing the problems of large-scale multi-agent command and control. While the near-term application of these tech-nologies is into military problem domains; the poster presentation is cleared for public release.
Published Version
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