In this paper, we describe our ongoing efforts to design a cognition-enabled industrial robotic workcell, which significantly increases the efficiency of teaching and adapting robot tasks. We have designed a formalism to match task parameter and input modality types, in order to infer suitable means for binding values to those parameters. All modalities are integrated through a graphical user interface, which a human operator can use to program industrial robots in an intuitive way by arbitrarily choosing modalities according to his or her preference.     «

In this paper, we describe our ongoing efforts to design a cognition-enabled industrial robotic workcell, which significantly increases the efficiency of teaching and adapting robot tasks. We have designed a formalism to match task parameter and input modality types, in order to infer suitable means for binding values to those parameters. All modalities are integrated through a graphical user interface, which a human operator can use to program industrial robots in an intuitive way by arbitraril...     »