Mobile robot systems usually are designed, built, and programmed for dedicated use cases. Consequently, especially for unmanned aerial vehicles diverse applications result in very heterogeneously designed robots. To overcome this need for specialization, we propose to dynamically adapt the robots' capabilities at run-time. This is done by connecting and disconnecting hardware modules providing those capabilities, i.e., re-allocating resources within the robot ensemble. Thereby, no longer individualized robots have to be designed for different tasks. Instead, the system is enabled to adapt its hardware configuration to changing requirements. For calculating necessary adaptations, i.e., solving the resource allocation problem, we propose a heuristic, marketbased approach that exploits the possibility to decompose the resource allocation problem and distributively finds a solution. We show that our approach outperforms a centralized one especially when increasing the problem size in terms of agents, tasks, and relevant capabilities while providing the same quality.

A key aspect of Industry 4.0 is the continuous interconnectedness of components. The standardized industrial communication protocol OPC UA offers a solution to this problem by enabling the exchange of data between the shop floor level and the inter-enterprise level. Due to the integration of the Time Sensitive Network (TSN) into OPC UA, it is now even possible to exchange information in real-time. Especially on the shop floor, there are numerous heterogeneous distributed devices from sensors to robots which must communicate with each other in real-time to achieve a distributed industrial control. Therefore, we propose an approach to combine real-time communication over TSN with OPC UA Programs to synchronize multiple distributed OPC UA Programs and exchange process data between them without losing real-time guarantees. This can be seen as the enabler of Plug-and-Produce with real-time requirements.

Industrial manufacturing is currently undergoing a transformation from mass production with inflexible production systems to individual production with adaptable cells. In order to ensure this adaptability of these systems, technologies such as plug & produce are needed, to integrate, modify and remove devices at runtime. Therefor an exact description of the system, the products and the capabilities / skills of the devices is essential as well as a network for communication between the devices. Deterministic data transmission is particularly important for distributed control systems. We propose an architecture for plug & produce mechanisms with hard real-time capable communication paths between the cyber-physical components using OPC UA PubSub over TSN and the ability to load and execute real-time critical tasks at runtime.

This paper presents the use of sensor-guided motions for robot-based component testing to compensate the robot's path deviations under load. We implemented two different sensorguided motions consisting of a 3D camera system to minimize the absolute deviation and a force/torque sensor mounted directly to the robot's end effector to minimize occurring transverse forces and torques. We evaluated these two sensor-guided motions in our testing facility with a classical tensile test and a heavy-duty industrial robot. From the obtained results, it can be stated, that transverse forces as well as the absolute deviation were significantly reduced.