Modelling Physical Human-Robot Interface with Different Users, Cuffs, and Strapping Pressures: A Case Study

Abstract

Assisting persons during physical therapy or augmenting their performance often requires precise delivery of an intervention. Robotic devices are perfectly placed to do so, but their intervention highly depends on the physical human-robot connection. The inherent compliance in the connection leads to delays and losses in bi-directional power transmission and can lead to human-robot joint axes misalignment. This is often neglected in the literature by assuming a rigid connection and has a negative impact on the intervention's effectiveness and robustness. This paper presents the preliminary results of a study that aims to close that gap. The study investigates what model forms and parameters best capture human-robot connection dynamics across different persons, connection designs (cuffs), and cuff strapping pressures. The results show that the linear spring-damper model is the best compromise, but its parameters must be adjusted for each individual and different conditions separately.