Résumé
This paper explores the synergistic application of the intrinsically stable MPC algorithm and human gait data retrieved via Xsens motion capture to optimize the geometric parameters of robot soles for mimicking human walking. Additionally, it investigates the use of an Ogden hyper-elastic model to determine the mechanical parameters of a soft component added beneath the robot soles to enhance stability and robustness when encountering small obstacles. Through a combination of control theory, our approach aims to achieve natural and stable robot locomotion in dynamic environments. Experimental results demonstrate the effectiveness of the proposed method in improving the walking performance and obstacle negotiation capabilities of the robot, paving the way for advancements in humanoid robotics and assistive technologies.