Mancisidor Aitziber, Zubizarreta Asier, Cabanes Itziar, Bengoa Pablo, Jung Je Hyung
IEEE Int Conf Rehabil Robot. 2017 Jul;2017:561-566. doi: 10.1109/ICORR.2017.8009307.
In order to enhance the performance of rehabilitation robots, it is imperative to know both force and motion caused by the interaction between user and robot. However, common direct measurement of both signals through force and motion sensors not only increases the complexity of the system but also impedes affordability of the system. As an alternative of the direct measurement, in this work, we present new force and motion estimators for the proper control of the upper-limb rehabilitation Universal Haptic Pantograph (UHP) robot. The estimators are based on the kinematic and dynamic model of the UHP and the use of signals measured by means of common low-cost sensors. In order to demonstrate the effectiveness of the estimators, several experimental tests were carried out. The force and impedance control of the UHP was implemented first by directly measuring the interaction force using accurate extra sensors and the robot performance was compared to the case where the proposed estimators replace the direct measured values. The experimental results reveal that the controller based on the estimators has similar performance to that using direct measurement (less than 1 N difference in root mean square error between two cases), indicating that the proposed force and motion estimators can facilitate implementation of interactive controller for the UHP in robotmediated rehabilitation trainings.
为了提高康复机器人的性能,了解用户与机器人之间相互作用所产生的力和运动至关重要。然而,通过力传感器和运动传感器对这两种信号进行常规直接测量,不仅会增加系统的复杂性,还会影响系统的可承受性。作为直接测量的替代方法,在这项工作中,我们提出了新的力和运动估计器,用于对上肢体康复通用触觉缩放仪(UHP)机器人进行适当控制。这些估计器基于UHP的运动学和动力学模型,并利用通过常见低成本传感器测量的信号。为了证明估计器的有效性,进行了多项实验测试。首先通过使用精确的额外传感器直接测量相互作用力来实现UHP的力和阻抗控制,并将机器人性能与所提出的估计器取代直接测量值的情况进行比较。实验结果表明,基于估计器的控制器与使用直接测量的控制器具有相似的性能(两种情况之间的均方根误差差异小于1 N),这表明所提出的力和运动估计器可以促进在机器人辅助康复训练中为UHP实现交互式控制器。