Research on UAV Autonomous Capability Rating Assessment Based on Entropy Weight-Objective Topologizable Modeling

Measuring the degree of autonomous capabilities of UAVs in a scientific and objective manner is crucial for assessing the state of UAV technology and directing future technological advancements. In this paper, the index system of the UAV autonomous capability level assessment is determined by using the gray correlation method. An expandable UAV autonomous capability level assessment model is constructed using the entropy weight-objective element approach, and the UAV autonomous capability level assessment is investigated from 24 indicators in three dimensions, including the human-computer interaction, task completion, and adaptive environment capabilities. A case study of the autonomous capability level assessment of a particular UAV model serves as an illustration of the scientificity and efficacy of the research conducted in this paper. The evaluation's findings demonstrate that the model can correctly represent the degree of autonomous capacity possessed by UAVs and offer useful benchmark data for enhancing such capability.