Control of Walking Assist Exoskeleton with Time-delay Based on the Prediction of Plantar Force
This addresses time-delay issues in lower-limb exoskeletons for walking assistance, representing an incremental improvement in control methods.
The researchers tackled the problem of time-delay in controlling walking assist exoskeletons by predicting future plantar force and walking status using LSTM and fully-connected networks, achieving confirmed prediction accuracy and precise assistance timing in experiments.
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.