Authors:
Jacob P. Buch
;
Lars C. Sørensen
;
Dirk Kraft
and
Henrik G. Petersen
Affiliation:
The Maersk Mc-Kinney Moller Institute and University of Southern Denmark, Denmark
Keyword(s):
Industrial Assembly Automation, Uncertainty Handling, Dynamic Simulation, Reuse of Experimental Data.
Related
Ontology
Subjects/Areas/Topics:
Industrial Automation and Robotics
;
Industrial Engineering
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Machine Learning in Control Applications
;
Modeling, Simulation and Architectures
;
Robotics and Automation
Abstract:
In this paper, we suggest a coherent way of representing results from experiments associated with robotic
assembly. The purpose of the representation is to be able to reuse the experiments in other assembly settings.
A main novelty in our representation is the inclusion of fine grained experimental uncertainties such as e.g.
deviations between a sensed object pose and the actual pose, and we discuss why it is very important for the
reusability of experiments to include these uncertainties. Under the reasonable assumption that we can represent
the uncertainties as a region around the origin in a potentially high dimensional Cartesian space, we show
that we can efficiently represent the studied deviations by storing experiments on a so called spherical lattice.
We illustrate that the representation works by studying simulation experiments on two different industrial use
cases involving grasping an object and mounting an object on a fixture.