Gait Planning of Hexapod Robot Based on Feedback Enhanced Hopf Oscillator

This paper studies a gait generation and switching method for a hexapod robot based on feedback-enhanced Hopf oscillators, exploring how to achieve gait transitions during planar walking by designing a coupling network. First, a coupled fully symmetric network model based on the improved Hopf oscillator was constructed. The CPG controller was used to transmit oscillator input signals to the hip joint, and a single-leg joint mapping function was designed to adjust the rotation angles of the knee and ankle joints. This approach improved the robot’s gait switching ability without affecting other gait characteristics. Furthermore, the influence of convergence coefficient combinations on network stability was analyzed, and an external feedback mechanism was introduced to enhance the oscillator’s adaptability, improving both gait switching performance and output stability. Joint simulations in Matlab and Gazebo were conducted to validate the effectiveness of the proposed gaitswitching method and the accuracy of joint design. The results demonstrate that this method achieves smooth gait transitions while significantly enhancing the motion flexibility and robustness of the hexapod robot. These experimental results provide a theoretical foundation for the application of hexapod robots on planar terrain and lay the groundwork for further dynamic gait optimization.