Interaction force and motion estimators facilitating impedance control of the upper limb rehabilitation robot

Abstract

Abstract-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.

Cable-driven lower limb rehabilitation robot

“…In the cases that the proposed structure is not working with value near of load cell mass, the force errors are less than 10%. From the literature, the errors forces found are similar to other prototypes rehabilitation devices [43][44][45][46][47] with errors less than 10% when using PID/trajectory control or impedance control. To compare, the commercial version of InMotion Arm Robot has a force resolution of 0.05 N [48] and a cost of more than USD 100,000 [49].…”

A review on the application of intelligent control strategies for post-stroke hand rehabilitation machines

“…In the force-based impedance control method, the robot reflects the end impedance characteristics of the robot by controlling the robot joint torque through feedback based on the contact force between the end and the environment. 58 In practical applications, the robot end position and contact force are detected in real time, and the grid feedback position and desired impedance model generate the desired force output, and the difference between the desired force and the actual contact force is taken, and the control torque is calculated by the robot dynamics model based on the force error as the joint driving force, so that the robot’s system behaves as the desired impedance model characteristics. Therefore, force-based impedance control must first determine an accurate kinetic model of the robot before the desired impedance model and accurate contact force control can be achieved.…”