Intelligent Locomotion Planning With Enhanced Postural Stability For Lower-Limb Exoskeletons

In this paper, an integrated control strategy is developed for both locomotion trajectory planning and posture stability, enabling shared autonomy between the human and lower-limb exoskeleton. Divergent component of motion (DCM) analysis was employed previously based on the linear inverted pendulum flywheel (LIPF) model to regulate the position of the center of mass (CoM) for humanoid robots. In this study, a new extended model is investigated for the DCM analysis by replacing the previous LIPF model, which is tailored for multi-degree-of-freedom (DOF) exoskeletons. This new model is designed to be personalized for each specific user's body by relaxing the assumption of having the total CoM at the hip joint in the previous LIPF model. Accordingly, the exoskeleton has the authority to ensure the posture stability and viability of locomotion in this human-robot interaction (HRI) by adjusting the upper body position using a DCM-based hip correction strategy. On the other hand, integrating adaptive central pattern generators (CPGs), the human has enough authority to modify the gait trajectories in real-time, while the amplitude and frequency of walking are constrained to their feasible ranges. The effectiveness of this intelligent HRI control for safe and stable locomotion is investigated through experimental studies on a lower-limb exoskeleton.