Future human deep space missions will place crews at increasing distances from Earth and present several challenges to overcome. Currently, ground teams entirely manage the spacecraft, helping astronauts with scheduling, procedure execution, estimation and interpretation of current state, and other tasks. As the distance from ground support increases, so does time lag in communications, increasingly requiring astronauts to independently work through problems such as diagnosis of critical faults in spacecraft systems and their corresponding cascade effects. This places a much higher cognitive burden on astronauts who must use multiple pieces of information from many different sources to identify and prioritize underlying issues. To meet these deep space support needs, SoarTech proposes the Virtual Explanation Reasoning Agent (VERA), a cognitive agent built on the Soar cognitive architecture and capable of helping humans solve problems in deep space missions through diagnostic reasoning, explanation, and learning. VERA will provide advanced state estimation and explanations for astronauts to help them more quickly, easily, and accurately identify and correct problems with spacecraft system, and will learn from its experience and interactions with astronauts and other information sources to improve its capabilities and resilience to novel, surprising, and evolving circumstances when updates from ground are unavailable.
AI diagnostic assistants for system operation, maintenance, repair, and troubleshooting in spacecraft and orbital systems.
AI diagnostic assistants for system operation, maintenance, repair, and troubleshooting in general aviation and any complex systems environment, including manufacturing, power generation, and medical systems.