Li Jinke, He Yong, Sun Jianquan, Li Feng, Ye Jing, Chen Gong, Pang Jianxin, Wu Xinyu
IEEE Trans Neural Syst Rehabil Eng. 2023;31:2111-2119. doi: 10.1109/TNSRE.2023.3268657. Epub 2023 Apr 27.
A large number of the WRLSs (wearable robots lumbar support) research have been presented for working efficient increase and injure risk reduction in recent years. However, the previous research can only complete the sagittal-plane lifting task, which can not adapt to the mixed lifting tasks in the actual work scene. Therefore, we presented a novel lumbar assisted exoskeleton with mixed lifting tasks by various postures based on position control, which can not only carry out the lifting tasks of sagittal-plane, but also complete the lifting tasks of sides. First, we proposed a new generation method of raising reference curves that can generate assistance curve for each user with each task, which is very convenient in mixed lifting tasks. Then, an adaptive predictive controller was designed to track the reference curves of different users under different loads, the maximum tracking errors of the angles are 2.2 and 3.3 respectively at 5kg and 15kg, and all the errors are within 3%. Compared to the condition of no exoskeleton, the average RMS (root mean square) of EMG (electromyography) for six muscles are reduced by 10.33±1.44% , 9.62±0.69% , 10.97±0.81% and 14.48±2.11% by lifting loads with stoop, squat, left-asymmetric and right-asymmetric respectively. The results demonstrate that our lumbar assisted exoskeleton presents outperformance in mixed lifting tasks by various postures.
近年来,为了提高工作效率和降低受伤风险,人们开展了大量关于可穿戴机器人腰部支撑(WRLSs)的研究。然而,以往的研究只能完成矢状面的提升任务,无法适应实际工作场景中的混合提升任务。因此,我们提出了一种基于位置控制的新型腰部辅助外骨骼,它能够通过各种姿势完成混合提升任务,不仅可以执行矢状面的提升任务,还能完成侧面的提升任务。首先,我们提出了一种新的生成参考曲线的方法,该方法可以针对每个用户的每项任务生成辅助曲线,这在混合提升任务中非常方便。然后,设计了一种自适应预测控制器来跟踪不同用户在不同负载下的参考曲线,在5kg和15kg负载时角度的最大跟踪误差分别为2.2和3.3,且所有误差均在3%以内。与无外骨骼的情况相比,通过弯腰、深蹲、左侧不对称和右侧不对称举升负载时,六块肌肉的肌电图(EMG)平均均方根(RMS)分别降低了10.33±1.44%、9.62±0.69%、10.97±0.81%和14.48±2.11%。结果表明,我们的腰部辅助外骨骼在各种姿势的混合提升任务中表现出色。