Abstract

Terrain classification and force assistance strategies in complex environments have always piqued the interest of many researchers. For wearable soft exosuits, inaccurate terrain recognition can easily introduce undesired assist forces that can easily injure the wearer. Because of these problems, we introduced a depth camera into the exosuit system, perform classification of terrain based on a Vision Transformer (ViT), and optimized the control algorithm, which is known as a ViT-Based Terrain Recognition System (TTRS). First, we used the Transformer algorithm to achieve a considerable classification effect in terrain recognition. We also introduced terrain recognition as prior knowledge into the force assistance strategy of the exosuit, providing different force assistance to the exosuit in different terrains. Subsequently, we performed human experiments with seven able-bodied people (six males and one female). The promising results demonstrate that our classification accuracy can reach 99.2% under six different terrains and that it can smoothly switch the force–assist curve in different terrains to better adapt to the complex terrain and improve the walking effect. The aforementioned terrain recognition algorithms and force–assist strategies may positively influence the study of soft exosuit, powered prostheses, and orthotics.

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