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Stochastic Optimal Shared Control With Non-Gaussian Processes, Paul Onor

Electrical and Computer Engineering ETDs

In this paper, we propose an approach for shared control of a planar quadrotor that allows for non-Gaussian disturbance in the model and non-Gaussian variation in the pilot's control actions. We do this by constructing empirical characteristic functions for the state, inputs, and disturbance using demonstrations by a human expert. These are then used to make predictions of future states and of the system disturbance, using the first and second moments of the empirical characteristic function to estimate the mean and variance of these processes. With this method, we can extend assumptions from additive white Gaussian noise to any real-valued …