PSM: A Predictive Safety Model for Body Motion Based On the Spring-Damper Pendulum

TL;DR

This paper introduces a predictive safety model using a spring-damper pendulum to assess human body safety in real-time, enhancing human-robot interaction and health monitoring by predicting safe orientations based on inertial data.

Contribution

The paper presents a novel predictive safety model (PSM) combining inertial measurements with a spring-damper pendulum to predict safe human body orientations in real-time.

Findings

Successfully verified the model in real-world scenarios.

Enables real-time safety assessment for human-robot interaction.

Supports health monitoring and assistive robotics applications.

Abstract

Quantifying the safety of the human body orientation is an important issue in human-robot interaction. Knowing the changing physical constraints on human motion can improve inspection of safe human motions and bring essential information about stability and normality of human body orientations with real-time risk assessment. Also, this information can be used in cooperative robots and monitoring systems to evaluate and interact in the environment more freely. Furthermore, the workspace area can be more deterministic with the known physical characteristics of safety. Based on this motivation, we propose a novel predictive safety model (PSM) that relies on the information of an inertial measurement unit on the human chest. The PSM encompasses a 3-Dofs spring-damper pendulum model that predicts human motion based on a safe motion dataset. The estimated safe orientation of humans is obtained by integrating a safety dataset and an elastic spring-damper model in a way that the proposed approach can realize complex motions at different safety levels. We did experiments in a real-world scenario to verify our novel proposed model. This novel approach can be used in different guidance/assistive robots and health monitoring systems to support and evaluate the human condition, particularly elders.