Stability Prediction Of Quadruped Robot Movement Using Classification Methods And Principal Component Analysis
Mohammad Divandari , Delaram Ghabi, Abdol Aziz Kalteh
DOI: 10.15598/aeee.v21i4.5215
Abstract
This paper introduces a novel technique for predicting the stability of quadruped robot locomotion using a central pattern generator (CPG). The proposed method utilizes classification methods and principal component analysis (PCA) to predict stability. The objective of this study is to anticipate the stability or instability of robot movement by modifying controlling parameters, referred to as features. The simulations of robot locomotion are conducted in MATLAB/SIMULINKtext{textregistered