A UAV-based Algorithm to Assist Ground SAR Teams in Finding Lost Persons Living with Dementia

Abstract

Unmanned Aerial Vehicles (UAV) are now used in many applications. Our focus in this paper is on their use in public safety, specifically in search and rescue (SAR) operations involving lost persons living with dementia (LPLWD). When it comes to saving lives, there are many human factors associated with UAV operations that impact the performance of expert human SAR that could be improved through forms of automation. These include tasks associated with piloting and search/flight management during SAR operations with the assistance of analysis performed on data from similar incidents in the past. A LPLWD may not be interested in assisting in their own rescue as they may not know they are lost. As such, it has been observed that they tend to keep walking until they are faced with an obstacle that bars their further progress. Knowing this behavior allows us to make predictions. Our approach in developing a people finding algorithm is to identify higher probability locations where an LPLWD might be found through informed, behavior-based analysis of the given terrain. We develop an algorithm to fly a UAV to the vicinity of these higher probability locations. We have validated our algorithm through field testing. In this paper, we present the results from both our data collection and the field tests. In addition, validation tests are presented and compared.