Dynamic GIS-Enabled Path Planning System for Disaster and Emergency Intervention in Urban Areas using Unmanned Ground Vehicle

Urban Search and Rescue (USAR) operations face critical challenges in dynamic, partially known environments where time is of the essence. This paper addresses the crucial problem of dynamic path planning for terrestrial vehicles in USAR, a domain where Unmanned Ground Vehicles (UGVs) offer significant advantages but remain under-represented in existing research compared to aerial solutions. We propose a novel system that integrates dynamic path planning, a Geographic Information System (GIS), and UGV technology, representing a significant advancement in USAR capabilities. Our solution, built upon the Command, Control, and Intelligence (C2I) architecture, employs a modified car-like mobile robot and a Java application leveraging ArcGIS APIs. This application efficiently computes the shortest path on a GIS map (using Esri World Roads data), dynamically recalculating routes in real-time as new obstacles are introduced, reflecting the evolving nature of disaster zones. Comparative evaluations against Google Maps and Google Earth validate the system’s ability to generate optimal and accurate paths, demonstrating its practical applicability for enhancing USAR response effectiveness.