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IEEE CIR: Cooperative Bayesian Intelligence for Aerospace Autonomy

March 10 @ 6:00 PM - 7:00 PM MST

As imperfectly designed agents in an uncertain world, autonomous systems will never work “out of the box” exactly as desired. By taking on tasks that push the technological limit, autonomous systems will encounter unexpected situations that go beyond their immediate capabilities. Autonomous systems must therefore be able to continuously and independently gather, process, and act on imperfect information. They must also be cognizant of what they can and cannot accomplish on their own and know when/how to seek help. In aerospace applications and beyond, scalable human-machine and machine-machine interactions will be essential for reinforcing the core perception, planning, learning, and reasoning algorithms that make machine autonomy on any one platform possible. This talk will discuss innovative Bayesian algorithmic approaches developed by the COHRINT Lab at CU Boulder that enable autonomous systems to opportunistically leverage different available kinds of human-machine and machine-machine interaction while performing challenging tasks in the presence of complex uncertainties. I will focus in detail on our group’s work on probabilistic modeling, inference, and optimization techniques for augmenting autonomous state estimation and decision-making algorithms running onboard autonomous systems with inputs from human teammates, task assistants and supervisors. I will describe how our approaches connect rigorous statistical modeling and learning techniques with “plug-and-play” semantic interfaces that can readily adapt to a variety of applications and users. Results from aerospace applications such as unmanned air/ground reconnaissance, missile defense, and space robotics will show how our methods allow human-machine systems to “cut knots and fill in gaps” in fundamentally novel ways for challenging problems. Co-sponsored by: Christopher Reardon, James Gowans, Yvonne Grey Speaker(s): Dr. Nisar Ahmed, 2155 East Wesley Avenue, Denver, Colorado, United States, 80208, Virtual: https://events.vtools.ieee.org/m/296059

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