A Three-Way Human-Robot Task Assignment Method under Intuitionistic Fuzzy Environment

Task assignment is a critical part of human-robot collaboration. The traditional task assignment methods in the intuitionistic fuzzy (IF) environment only consider two options, i.e., the task is executed by humans or machines. However, some tasks may need to be completed by humans and machines working together, such as mecha. Therefore, we propose a human-robot task assignment method under the IF environment based on three-way decision (3WD) theory in this paper. By extending the traditional two-way assignment mode into the three-way one, our method can flexibly deal with the concerned situations. At first, the appropriateness of assigning each task to the machine is calculated by IF TOPSIS. When ranking the IF evaluation values, the decision maker's attitude toward uncertainty is considered. Then the appropriateness served as conditional probability and a cost-sensitive IF 3WD model is constructed to complete the assignment. Furthermore, we construct algorithms to deal with dynamic situations. Finally, a numerical example illustrates the feasibility of the proposed method.