Nowadays, wiring in control cabinets is a manual, time-consuming, and error-prone assembly task, therefore automation offers great potential for improvement. However, the wiring is a highly complex assembly task involving hundreds of deformable linear objects (DLOs). Currently, existing fully automated approaches to solving this task commonly involve complex system setups and still have technical shortcomings in terms of handling resource capabilities and in-parallel execution. Hence, human-robot collaboration (HRC) can be a cost-effective approach if both the sub-tasks for the human and the robot are optimally allocated. In this paper, a task allocator is presented towards optimizing one human-robot collaborative system setup within control cabinet assembly. Based on a series of experiments, the potential for improvement in the cabling of control cabinets using an HRC paradigm is investigated. To this end, the solution is being validated against industry-related key performance indicators (KPIs).
Glykos et al. (2026) studied this question.