Moubarak S, Pham M T, Moreau R, Redarce T
Institut National des Sciences Appliquées (INSA) de Lyon, 69621 Villeurbanne Cedex, France.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:4489-93. doi: 10.1109/IEMBS.2010.5626036.
This paper presents a new gravity compensation method for an upper extremity exoskeleton mounted on a wheel chair. This new device is dedicated to regular and efficient rehabilitation training for post-stroke and injured people without the continuous presence of a therapist. The exoskeleton is a wearable robotic device attached to the human arm. The user provides information signals to the controller by means of the force sensors around the wrist and the arm, and the robot controller generates the appropriate control signals for different training strategies and paradigms. This upper extremity exoskeleton covers four basic degrees of freedom of the shoulder and the elbow joints with three additional adaptability degrees of freedom in order to match the arm anatomy of different users. For comfortable and efficient rehabilitation, a new heuristic method have been studied and applied on our prototype in order to calculate the gravity compensation model without the need to identify the mass parameters. It is based on the geometric model of the robot and accurate torque measurements of the prototype's actuators in a set of specifically chosen joint positions. The weight effect has been successfully compensated so that the user can move his arm freely while wearing the exoskeleton without feeling its mass.
本文提出了一种用于安装在轮椅上的上肢外骨骼的新型重力补偿方法。这种新装置致力于为中风患者和受伤人员提供定期且高效的康复训练，无需治疗师持续在场。外骨骼是一种附着在人手臂上的可穿戴机器人设备。用户通过手腕和手臂周围的力传感器向控制器提供信息信号，机器人控制器针对不同的训练策略和模式生成适当的控制信号。这种上肢外骨骼涵盖了肩部和肘关节的四个基本自由度以及三个额外的适应性自由度，以匹配不同用户的手臂解剖结构。为了实现舒适且高效的康复，我们研究了一种新的启发式方法并将其应用于我们的原型，以便在无需识别质量参数的情况下计算重力补偿模型。它基于机器人的几何模型以及在一组特定选择的关节位置对原型执行器的精确扭矩测量。重量影响已成功得到补偿，这样用户在穿戴外骨骼时可以自由移动手臂而感觉不到其重量。
