Abstract
This paper presents a statistical-economic model for evaluating robot precision as measured by its positional repeatability. The model formulated assumes that repeatability follows a Rayleigh distribution. An economic measure maximizing the expected profit per unit time is developed, leading to an optimal velocity solution for a given task. Additional properties of the solution and sensitivity analyses are also provided. Finally, the model is validated by an empirical study of a simulated multi-station assembly operation with a PUMA robot that meets a random set of task requirements.
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