Visual Programming of Robot Tasks with Product and Process Variety

Abstract

Abstract In flexible manufacturing settings, automation is shaped by ever changing conditions (e.g. varying part feeding locations, highly customizable products). Quick adaptation of robot systems is mostly achieved by visual end-user robot (re-)programming. In this paper, we discuss the explicit integration of anticipated product and process variety into visually programmed tasks. We contribute a task model which captures a user-defined range of task variants. To this end, parts are specified in terms of approximate locations and generalized parts families. Workspace exploration and combinatorial assignment planning enable online adaptation to unknown environments. Our experiments show that this adaptation capability can increase the economical efficiency of cobot use.