Various exoskeleton robots are being developed according to users’ conditions. Lower limb exoskeleton robots have attracted much attention for performing walking motions, a basic exercise for paralyzed patients. In this study, the walking environment of an exoskeleton robot wearer who walks using a crutch is identified as the foot position of the crutch support point and the support leg; therefore, the upcoming foothold location is calculated and sets as a control target. Rather than using preset pedestrian patterns, pedestrian patterns that can match the environment are created using the dynamic movement primitives machine learning technology. We evaluated the exoskeleton robot through an experiment with a healthy 29-year-old male. The experimental results showed that the exoskeleton robot was able to demonstrate the adaptive strides according to the wearer’s intention.

根据用户的条件，正在开发各种外骨骼机器人。下肢外骨骼机器人在进行步行运动时引起了很多关注，步行运动是瘫痪病人的基本运动。在本研究中，将使用拐杖行走的外骨骼机器人佩戴者的行走环境确定为拐杖支撑点和支撑腿的脚部位置；因此，将计算即将到来的立足点位置并将其设置为控制目标。使用动态运动原语机器学习技术创建可以匹配环境的行人模式，而不是使用预设的行人模式。我们通过与29岁健康男性进行的实验评估了外骨骼机器人。