Active fall prevention: robotic vision in AAL

TL;DR

This paper introduces a robotic vision system for proactive fall risk detection in elderly homes, aiming to prevent falls before they happen and enhance safety.

Contribution

It presents a novel active detection and classification system using a service robot with vision sensors for fall risk assessment.

Findings

Effective hazard classification improves robot task performance.

System enhances elderly safety through proactive fall risk detection.

Potential to reduce fall incidents in home environments.

Abstract

Effective methods of preventing falls significantly improve the quality of life of the Elderly. Nowadays, people focus mainly on the proper provision of the apartment with handrails and fall detection systems once they have occurred. The article presents a~system of active detection and classification of the risk of falls in the home space using a~service robot equipped with a~vision sensor. Hazard classification allows for effective performance of tasks assigned to the robot while maintaining a~high level of user safety.