Intelligent decision making algorithm for path planning based on reference Linguistic Fuzzy set

This paper proposes a novel path planning algorithm called Reference Linguistic Fuzzy Algorithm (RLFA); moreover, the parametric analysis procedure of the RLFA is described in this paper. It finds the optimal path by calculating the decision value required by path planning. However, most of the research ignores the issue of equal decision scores. The proposed algorithm has been compared to the original distance metrics, the fuzzy synthetic evaluation method, the modified three-way TOPSIS method, and the Generalized TODIM method. Compared with the existing algorithms, the algorithm proposed in this paper improves the reliability of path planning decision making and eliminates the defects of the traditional algorithms, which rely on parameter settings. It combines subjective and objective dual evaluation perspectives to correct the possible bias in the single subjective perspective. This paper is supported by experimental validation, and the results show that the proposed algorithm can achieve the optimal solution under all conditions.