On-line Dynamic Gait Generation Model for Wearable Robot with User’s Motion Intention

In this paper, an on-line dynamic gait generation model is proposed, which makes it possible to plan real-time gait trajectories in continuous motion process online. The model enables wearers to perform complex movements in different scenes with the help of an exoskeleton robot. Meanwhile, based on multi-sensor fusion, a method is designed to detect the wearers’ movement intention. The gait trajectories generated by the proposed algorithm are applied to the lightweight lower-limb exoskeleton robot (LLEX). The experimental results show that the algorithm can accurately and effectively plan wearers’ movement trajectories of lower limbs, and freely perform various gait patterns, indicating the described algorithm is credible enough to generate dynamic gait patterns for wearable exoskeleton robots.