A Technique for End-Effector Force Estimation in Parallelogram Arm Robot using Link-Integrated Load Cells

Abstract

In end effector rehabilitation robots, user effort is usually measured using highly accurate, but expensive, multi-axis force/torque (F/T) sensors. These sensors are not easily available in developing countries. An alternative force sensing method, making use of low-cost load cells mounted on the active links, is presented. In this study, a model of a robot using the proposed sensing technique was developed, with the placement of the load cells justified using kinematic and dynamic analyses. The relationship between the force applied at the end effector, and force experienced by the load cells was determined. Preliminary experimental validation of the ability to estimate end effector force from the link-integrated load cells was carried out using finite element analysis in SolidWorks. Initial evaluation of tracking accuracy resulted in an average root-mean-square error (RMSE) of 0.566. The application of compensators generated from polynomial regressors resulted in over 300% improvement in performance, resulting in an average RMSE of 0.053. The results show that proposed technique can be used to accurately estimate forces at the end effector at relatively low costs.