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On the theory side, this is related to the Nyquist Sampling Rate, which is how frequently you must measure a single to get an accurate reconstruction of it's peaks / valleys. Not suprisingly, Nyquist as a name appears all over some fundamental results in optimal control like the nyquist stability theorem. I suspect the insight you are looking for is right ...


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This seems like an interesting question! Read it once and haven't put a ton of thought into this, but my gut reaction was a disturbance model. Suppose you had some optimal path, $P$. Your path planning could be attempting to map that optimal path, but the calculated path might be constantly updating based on noise in sensor readings, localization estimates, ...


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