ROApr 9, 2017

A Distributed Control Framework for a Team of Unmanned Aerial Vehicles for Dynamic Wildfire Tracking

arXiv:1704.02630v1109 citations
Originality Synthesis-oriented
AI Analysis

This addresses the dangerous and costly task of wildfire tracking for emergency responders, but appears incremental as it builds on existing UAV and control methods.

The paper tackled the problem of monitoring wildfires by proposing a distributed control framework for a team of UAVs to track fire fronts, with experimental results demonstrating capabilities in covering a spreading wildfire.

Wildland fire fighting is a very dangerous job, and the lack of information of the fire front is one of main reasons that causes many accidents. Using unmanned aerial vehicle (UAV) to cover wildfire is promising because it can replace human in hazardous fire tracking and save operation costs significantly. In this paper we propose a distributed control framework designed for a team of UAVs that can closely monitor a wildfire in open space, and precisely track its development. The UAV team, designed for flexible deployment, can effectively avoid in-flight collision as well as cooperate well with other neighbors. Experimental results are conducted to demonstrate the capabilites of the UAV team in covering a spreading wildfire.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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