Human-in-the-Loop Control of a Wearable Lower Limb Exoskeleton for Stable Dynamic Walking

Exoskeletons are increasingly used to assist humans in military, industry, and healthcare applications, thereby enabling individuals to gain increased strength and endurance. This article proposes a novel human-in-the-loop control framework for a fully actuated lower limb exoskeleton with high degree-of-freedoms (DoFs), allowing users to walk without crutches or other external stabilization tools. To imitate the natural lower limb motion of users, a novel barrier energy function is utilized for the design of the control strategy, where the human-robot manipulation space is reformulated as a human-voluntary and a robot-constrained region. The variations in the barrier energy function are based on the distance between the center of mass and zero moment point of the walking exoskeleton, thereby constraining the lower limb motion of the user to a compliant region around various desired trajectories. Based on varying regional functions, the proposed strategy is designed to control the exoskeleton to follow appropriate ergonomic trajectories. For such a purpose, an adaptive controller is exploited considering the functions of the human effort and the robot's capabilities simultaneously, and a smooth motion transition can be achieved between the human and robot regions. Finally, physical experiments are conducted on a ten-DoFs walking exoskeleton to validate the stability and robustness of the proposed control framework with subjects performing flat walking, turning, and obstacle avoidance movements.

Automated summary

This article proposes a novel human-in-the-loop control framework for a fully actuated lower limb exoskeleton, allowing users to walk without external stabilization tools. The control strategy is designed to imitate the natural lower limb motion of users through barrier energy function and regional functions. The proposed strategy controls the exoskeleton to follow appropriate ergonomic trajectories using an adaptive controller considering human effort and robot capabilities.