Multi-Terrain Adaptive Control for Knee Exoskeletons: Development and Experimental Evaluation

Lower limb augmented exoskeletons (LLAE) could potentially be used in some domains (e.g. logistics) to enhance human walking ability. For walking with LLAE on different terrains, precise and flexible control strategies of LLAE are required to achieve smooth and natural motion transitions. However, previous control algorithms for LLAE are mainly developed for flat terrains, so the LLAE cannot be effectively used in work environments with other terrains such as slopes and stairs. Therefore, a multi-terrain adaptive assist algorithm based on parametric dynamic motion primitives (PDMPs), which can adaptively adjust assist torques according to terrain types, was developed in this paper to solve the above problems. The algorithm obtains the mapping relationship between the assistance sub-model and terrain slope for each terrain by polynomial fitting, thus modelling the multi-terrain adaptive assist algorithm based on PDMPs. The model is evaluated using a generalized validation method and the results show that the peak error in torques prediction of the model is less than 5%. To further validate the effectiveness of the proposed algorithm, it was verified on a homemade LLAE and the experimental results showed that the proposed multi-terrain adaptive assist algorithm was able to reduce the human body's motion consumption by about 5%, which can facilitate the exoskeleton system to achieve the human-exoskeleton cooperative control.