Flexible skill-based control for robot cells in manufacturing - Wiese, Torben; Abicht, Johannes; Friedrich, Christian; Hellmich, Arvid; Ihlenfeldt, Steffen (Frontiers in Robotics and AI, 2022)
Decreasing batch sizes lead to an increasing demand for flexible automation systems in manufacturing industries. Robot cells are one solution for automating manufacturing tasks more flexibly. Besides the ongoing unifications in the hardware components, the controllers are still programmed application specifically and non-uniform. Only specialized experts can reconfigure and reprogram the controllers when process changes occur. To provide a more flexible control, this paper presents a new method for programming flexible skill-based controls for robot cells. In comparison to the common programming in logic controllers, operators independently adapt and expand the automated process sequence without modifying the controller code. For a high flexibility, the paper summarizes the software requirements in terms of an extensibility, flexible usability, configurability, and reusability of the control. Therefore, the skill-based control introduces a modularization of the assets in the control and parameterizable skills as abstract template class methodically. An orchestration system is used to call the skills with the corresponding parameter set and combine them into automated process sequences. A mobile flexible robot cell is used for the validation of the skill-based control architecture. Finally, the main benefits and limitations of the concept are discussed and future challenges of flexible skill-based controls for robot cells are provided.