Evaluation and Fault Classification for Service Robot during Sit- to-Stand Movement through Center of Mass

Abstract

Many service robots have been developed to assist patients with sit-to-stand movement (STS). However, little research has focused on users’ negative psychological changes during the STS movement when assisted by a robot. The STS movement accompanied with a negative psychological change is defined as a fault. The main purpose of this study was to propose a method of conveying faults to a service robot through the center of mass (CoM). Experiments on the STS movement were executed five times with 10 healthy subjects under four conditions: two self-performed STSs with seat heights of 43 and 62 cm, and two robot-assisted STSs with a seat height of 43 cm and end-effector speeds of 2 and 5 s. Time series data on the CoM were measured with high-speed camera system. A classifier was designed according to the data on the CoM in the frequency domain. The results showed that the proposed classifier had a high probability of discriminating fault classes from others. Then, the vertical ground reaction force (vGRF) under the same experimental conditions was used to cross-check the experimental results. It was concluded that faults in the assistance of service robots can be detected from the CoP-related items.