上肢康复机器人异构运动映射方法

Heterogeneous Motion Mapping Method for Upper-Limb Rehabilitation Robot

  • 摘要: 提出一种康复机器人以健肢的运动位姿为参照带动患肢进行康复训练的方法。该方法使得机器人的运动轨迹更符合患者自身的运动习惯,实现康复训练的个性化,锻炼患者双侧肢体的协调性,提高康复训练效果。设计了一种4自由度气动上肢外骨骼康复机器人,由于机器人和上肢的自由度不同,提出了主从异构的运动映射算法。采用指数积法建立机器人运动学模型,定义机器人的等同生理关节,进行健肢和机器人之间位姿映射。对于关节活动度训练,设计了基于四元数的姿态解算和镜像求解的位置映射算法,利用健肢的独立运动关节姿态实现人- 机器人之间等同关节的映射,提高映射效率。在多关节参与的日常生活活动(Activity of Daily Living,ADL)训练中,提出了肘腕分离的运动映射方法,分别以健肢大臂和小臂刚体的向量运动解算机器人肩部两个关节与肘部1个关节的旋转运动,保证了运动映射过程中的位姿精度。最后,设计康复运动跟随实验和位姿相似度验证实验,证明主从异构运动映射方法的可行性。

     

    Abstract: A method that enables rehabilitation robots to train affected limbs by referencing the motion postures of healthy limbs is proposed in this study. This method ensures that the trajectory of the rehabilitation robot aligns very closely with the target patient′s motion habits, personalizes rehabilitation training, exercises the coordination of the patient′s bilateral limbs, and improves the effect of the training. In this study, a four-degree-of-freedom pneumatic upper limb exoskeleton rehabilitation robot is designed, and a master-slave heterogeneous motion-mapping algorithm is proposed to deal with the different degrees of freedom of the robot and upper limb. The exponential product method is used to establish the robot kinematic model, define the equivalent physiological joints of the robot, and perform position mapping between the healthy limb and the robot. For joint mobility training, a position mapping algorithm characterized by quaternion-based pose and mirror solving is developed to realize equivalent human-robot joint mapping by leveraging the independent kinematic joint poses of healthy limbs to improve the mapping efficiency. In the activities of daily living training involving multiple joints, the motion mapping method for elbow-wrist separation is proposed. The proposed motion-mapping method solves the rotational motions of two joints at the shoulder and one joint at the elbow of the robot using the vectorial motions of the large and small arm rigid bodies of the healthy limb, respectively, and ensures positional accuracy during motion mapping. Finally, rehabilitation motion following and position similarity verification experiments are conducted to verify the feasibility of the master-slave heterogeneous motion mapping method.

     

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