Advanced Filtering in Intuitive Robot Programming

Abstract

This text deals with the problem of reducing multi-dimensional data in the context of programming an industrial robot. Different ways to treat the positional and orientational data are discussed, and algorithms for each of these are developed and tested on various generated datasets. The outcome of the work was an algorithm expressing the position as three polynomials, one for each coordinate, and the orientation is then reduced with respect to given tolerances in Euler Angles. The resulting algorithm turned out to reduce a physical dataset with 97%. It was concluded that it is very satisfying to be able to reduce a set with this amount without loosing vital information.