24/7 Elderly Guard Robot: Emergency Detecting, Reacting, and Reporting

Abstract

As the number of elderly persons increases, greater attention must be given to how they or their caregivers deal with emergency situations. This paper describes an automated tracking, fall detection, and emergency recovery system for elderly persons, and shows that efficient a Socially Assistive Robot (SAR) can resolve emergency situations and abnormal behaviors for at-risk populations. Our assistant robot uses position data provided by Ultra-WideBand (UWB) wireless network and motion sensor information to detect potentially dangerous situations for elderly persons. In this context, a deep neural network-based double-check method has been developed to detect and confirm fall situation with high accuracy using in-house developed sensory hardware. We then simulated four typical emergency scenarios using SILBOT-3 robot. Interaction scenarios were demonstrated to 28 caregivers, who were then invited to complete a short questionnaire regarding benefits and improvements for our system. Caregivers responded positively to our system's performance and stated that they would accept an assistant robot that could notify them quickly about a dangerous situation or possibly resolve the situation autonomously.