Design of social navigation quality evaluation model based on combined weight

Abstract

Based on the human–robot interaction behavior of mobile robots in social navigation, this paper proposes a social navigation quality evaluation model based on combined weights for the problems of single indicators, rough quantification and non-convergence of information in social navigation quality evaluation. Firstly, three evaluation modules of comfort, naturalness and sociality are designed, and each module is refined into primary and secondary indicators. The robot path navigation data are calculated by the indicator quantification formula. Secondly, the subjective and objective weights of hierarchical analysis method and the entropy weight method are combined to determine the index weights at each level. The weighted sum is used to achieve the fusion of index information and obtain the optimal solution of the evaluation navigation algorithm. Finally, we simulate the social scene through visualization simulation experiments to obtain the trajectory data of the robot in the social scene. The experimental results verify the feasibility of the theoretical model and give the final scores and optimization opinions of the tested algorithms. Through the evaluation of the social navigation quality evaluation model, the path planning algorithm that best suits the comfort perception of pedestrians in the current scenario can be found in the tested algorithms.