Modeling of Leg Coupling Dynamics and Intelligent Optimal Control for Quadruped Robots

In recent years, quadruped robots have received many attention due to excellent adaptability in complex terrains,and the key to their stable locomotion lies in gait coordination. But,the traditional central pattern generator (CPG) models often face challenges such as high reliance on manual experience for tuning coupling parameters and poor adaptive capability. To address this problem, this study proposes a control method integrating coupling dynamics modeling and intelligent optimization. And,a four-leg coupling dynamics model based on Hopf nonlinear oscillator is constructed, in which coupling matrix describes inter-leg phase relationships. The matrix is automatically optimized by incorporating a genetic algorithm and implementing global search with a phase synchronization stability metric as the fitness function. Simulation results show that the optimized coupling parameters significantly improve the phase coordination ability of the four-leg oscillators. This effective eliminates phase deviations under natural dynamics, and greatly enhances both gait synchrony and stability.And so,the study contributes to the autonomous adaptability of quadruped robots by providing a data-driven global optimization framework for their gait control.\