Empirical modeling and comparison of robotic tasks

How can we describe and measure real robotic systems? Implemented robotic systems for intelligent tasks are are often extremely complicated, depending not only on `interesting´ theoretical parameters and models, but on many assumptions and constants which may be set almost arbitrarily. In order to evaluate and compare systems which employ diverse components and methods, we are obliged to employ empirical, performance based methods. We model task implementations as particular parameterizations of the task goals they represent. Through fractional factorial experiments and analysis of variance we establish the statistically significant parameters and parameter interactions for a pair of part-orienting tasks. Sensitivity analysis determines optimal parameter values and reveals relationships among parameters as they affect task performance