Exploiting Arch-like Foot Structure for Knee-Extended Walking in Bipedal Robots

This paper investigates the locomotion of bipedal robots, with a focus on knee-extended walking. While knee joint extension is essential for efficient human walking, humanoid robots face challenges such as pose singularities, and traditional control methods often result in high joint velocities. To address these issues, static approaches have been proposed to achieve knee-extended walking. In this study, we present a pattern generation method based on the inertial linear inverted pendulum model (ILIPM) to simulate human arch motion. A quadrilateral foot structure and compliant control of the virtual leg are designed to enable knee-extended walking in biped robots. To enhance stability, we combine linear feedback control with an ankle joint strategy to correct the deviation of the divergent component of motion (DCM). Experimental comparisons were conducted across three scenarios: bent-knee walking, knee-extended walking without compliance control, and knee-extended walking with compliance control. The results show that knee-extended walking with compliance control results in the lowest energy consumption and minimizes the root mean square error (RMSE) of the center of mass (COM) velocity oscillations. Additionally, ILIPM-based walking experiments demonstrate smooth periodic oscillations of the COM trajectory with an amplitude of approximately 0.015 m. In the comparison of LIPM, Flywheel LIPM, and ILIPM, the ILIPM approach showed the least impact on the COM posture angle and angular momentum, leading to improved walking stability. Finally, DCM error correction experiments revealed that combining ankle joint control with linear feedback control provides the most effective correction of DCM errors.