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: Autonomous systems use closed-loop feedback of sensed or communicated information to meet desired objectives. Meeting such objectives is more challenging when autonomous systems are tasked with operating in uncertain complex environments with intermittent feedback. This presentation explores different analysis methods that quantify the effects of intermittent feedback with respect to stability and performance of the autonomous agent. Various scenarios are considered where the intermittency results from natural phenomena or adversarial actors, including purposeful intermittency to enable new capabilities. Specific examples include intermittency due to occlusions in image-based feedback and intermittency resulting from various network control problems.
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