Presented is a quantifiable method by which the behaviors of robots, as determined by their performance in a cyber-physical context, can be captured and generalized so that accurate predictions of sequentially coordinated multirobot behaviors can be made. The analysis technique abstracts sequentially coordinated multirobot missions as a frequentist inference problem. Rather than attempt to identify and put into a causal relation all the hidden and unknown cyber-physical influences that can have an impact on mission performance, we model the problem as that of predicting multirobot performance as a conditional probability. This allows us to initially limit the testing and evaluation of robot performance to evaluations of atomistic behaviors, and to experiment mathematically with the combinations of predictive features and elementary performance metrics to derive accurate predictions of higher level coordinated performance.
Collaborators: Joseph Giampapa, John Dolan, Kawa Cheung.
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