Many kinds of lower-limb exoskeletons were developed for walking assistance. However, when controlling these exoskeletons, time-delay due to the computation time and the communication delays is still a general problem. In this research, we propose a novel method to prevent the time-delay when controlling a walking assist exoskeleton by predicting the future plantar force and walking status. By using Long Short-Term Memory and a fully-connected network, the plantar force can be predicted using only data measured by inertial measurement unit sensors, not only during the walking period but also at the start and end of walking. From the predicted plantar force, the walking status and the desired assistance timing can also be determined. By considering the time-delay and sending the control commands beforehand, the exoskeleton can be moved precisely on the desired assistance timing. In experiments, the prediction accuracy of the plantar force and the assistance timing are confirmed. The performance of the proposed method is also evaluated by using the trained model to control the exoskeleton.

中文翻译：

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基于足底力预测的时滞辅助步行外骨骼控制

开发了多种下肢外骨骼用于辅助行走。然而，在控制这些外骨骼时，由于计算时间和通信延迟导致的时间延迟仍然是一个普遍问题。在这项研究中，我们提出了一种通过预测未来足底力和步行状态来防止控制步行辅助外骨骼时出现时间延迟的新方法。通过使用长短期记忆和全连接网络，可以仅使用惯性测量单元传感器测量的数据来预测足底力，不仅在步行期间，而且在步行开始和结束时。根据预测的足底力，还可以确定步行状态和所需的辅助时机。通过考虑延时和预先发送控制命令，外骨骼可以在所需的辅助时间精确移动。在实验中，证实了足底力和辅助时机的预测精度。还通过使用经过训练的模型来控制外骨骼来评估所提出方法的性能。