Algorithm for evaluating the stability of mechanical structure of a triphibian robot based on reduced-dimensional fuzzy C-mean clustering

Abstract The current mechanical structure stability assessment algorithm obtains the assessment results by selecting a large number of indicators and assigning weights to them, which leads to low assessment accuracy and complex processing of the assessment algorithm due to the relatively complex and high dimensional selection of indicators. In response to the above analyzed problems, the stability assessment algorithm of the mechanical structure of the triphibian robot based on reduced-dimensional fuzzy C-mean clustering will be studied. Based on the analysis of the stability of the mechanical structure of the triphibian robot, the factors affecting the stability of the mechanical structure are obtained. The stability assessment factors are dimensionalized using PCA dimensionality reduction method. The FCM algorithm uses the dimensionalized assessment factors to process the robot related data and obtain the stability assessment results. The experimental results of the evaluation algorithm show that the proposed evaluation algorithm improves the evaluation accuracy by at least 21% through the dimensionality reduction of the evaluation metrics, and the evaluation effect is better.