Control flow for robust one-shot robot programming using entity-based resources

Abstract

Robotic systems are used in a wide range of applications. With an intuitive programming system from previous work we are able to transfer the advantages of robotic systems into more unstructured environments like private households or small and medium sized enterprises. An important challenge in this field is to enable non-experts to use all the capabilities of a robot. This includes two aspects: Robots must be intuitive to program and robust to execute. Our recently presented One-Shot programming framework concerns both aspects. The main contribution of this work is to extend the existing framework and to raise the usability of our approach. With this motivation we identify generalization chances in our task representation model and introduce an extension of our programming paradigm by integrating control flow to increase its capabilities. The proposed system concept enables users to guide a robot kinesthetically through a task without prior knowledge. By observing resources in the workspace, the demonstrated task is encoded as a finite state machine (FSM). This FSM allows the reproduction of a task by the robot itself and also offers two ways to control the flow of a robot program: Loops and Branches. With these statements a non-expert user gains the opportunity to program even more complex task solutions.