Optimizing human–robot task allocation using a simulation tool based on standardized work descriptions

Abstract

Human–robot collaboration is enabled by the digitization of production and has become a key technology for the factory of the future. It combines the strengths of both the human worker and the assistant robot and allows the implementation of an varying degree of automation in workplaces in order to meet the increasing demand of flexibility of manufacturing systems. Intelligent planning and control algorithms are needed for the organization of the work in hybrid teams of humans and robots. This paper introduces an approach to use standardized work description for automated procedure generation of mobile assistant robots. A simulation tool is developed that implements the procedure model and is therefore capable of calculating different objective parameters like production time or ergonomics during a production cycle as a function of the human–robot task allocation. The simulation is validated with an existing workplace in an assembly line at the Volkswagen plant in Wolfsburg, Germany. Furthermore, a new method is presented to optimize the task allocation in human–robot teams for a given workplace, using the simulation as fitness function in a genetic algorithm. The advantage of this new approach is the possibility to evaluate different distributions of the tasks, while considering the dynamics of the interaction between the worker and the robot in their shared workplace. Using the presented approach for a given workplace, an optimized human–robot task allocation is found, in which the tasks are allocated in an intelligent and comprehensible way.