An AI-Based Decision-Making Framework with Task Planning and Dynamic Reconfiguration Capabilities

This paper proposes a decision-making framework based on Artificial Intelligence (AI) functionalities for the dynamic planning and control of human-robot collaborative (HRC) scenarios both on the design and execution phase. Allocation of tasks among resources is being investigated based on user-defined metrics prioritized according to importance. Integration with a digital simulation tool is presented in order to take into account alternative scenarios and define the optimal solution. The proposed framework is applied in tandem with a central orchestrator in order keep track of the real execution status and dynamically reconfigure the provided plans upon request. The solution is validated in a case study derived from white goods industry where the operator is working under a collaborative environment with a robot in order to perform a defined assembly.