Choi, Younghoon (Georgia Institute of Technology), Choi, Youngjun (Georgia Institute of Technology), Briceno, Simon (Georgia Tech), Mavris, Dimitri (Georgia Institute of Technology)

Multi-UAS Path-Planning for a Large-Scale Disjoint Disaster Management

Scheduled for presentation during the Regular Session "Path Planning IV" (ThB1), Thursday, June 13, 2019, 14:10−14:30, Heritage B

2020 International Conference on Unmanned Aircraft Systems (ICUAS), June 11-14, 2019, Athens, Greece

This information is tentative and subject to change. Compiled on April 26, 2024

Abstract

A UAS-based disaster management method has been adopted to monitor the disaster impact and protect human lives since it can be rapidly deployed, execute an aerial imaging mission, and provide a cost-efficient operation. In the case of a wildfire disaster, a disaster management is highly complex because of large-scale wildfires that can occur simultaneously and disjointly in a large area. In order to effectively manage these large-scale wildfires, it requires multiple UAS with multiple ground stations. However, conventional UAS-based management methods relies on a single ground station that can have a limitation to handle the large-scale wildfire problem. This paper presents a new path-planning framework for UAS operations including a fleet of UAVs and multiple ground stations. The framework consists of two parts: creating coverage paths for each wildfire and optimizing routes for each UAV. To test the developed framework, this paper uses representative wildfire scenarios in the State of California.