基于核化运动基元的外骨骼膝关节步态轨迹在线规划

Online Gait Trajectory Planning of a Knee Exoskeleton Robot Based on Kernelized Movement Primitives

为了提高外骨骼机器人的适应性与人机交互安全性,提出了一种基于核化运动基元的步态轨迹规划算法,可根据使用者步态状态实时调整步态轨迹。在外骨骼膝关节上对算法进行了验证。结果表明,利用小样本量训练数据,算法能够通过在线调整形状参数,保证预测轨迹与参考轨迹的形状相似;通过实时检测步态相信息,并在期望点处对步态轨迹进行在线调整,可生成适应使用者状态变化的运动轨迹。

In order to improve the adaptability of an exoskeleton robot and the safety of human-exoskeleton interaction,an online gait trajectory planning method based on kernelized movement primitives(KMPs) is proposed, which can adjust the gait trajectory in real time according to the user’s gait state. The algorithm is demonstrated on a knee joint exoskeleton.The result shows that the proposed algorithm can adjust the shape parameters online according to a few training samples, to ensure that the predicted trajectory is similar to the original trajectory. It can also generate a trajectory according to user’s state change by detecting gait phase in real time and adjusting the gait trajectory online at the desired point.