A Distributed Deep Learning Approach for A Team of Unmanned Aerial Vehicles for Wildfire Tracking and Coverage
Author:
Affiliation:
1. Amazon Robotics Research
2. University of Nevada,Advanced Robotics and Automation (ARA) Lab,Department of Computer Science and Engineering,Reno,USA
3. University of Nevada,Department of Mechanical Engineering,Reno,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10023545/10022323/10023709.pdf?arnumber=10023709
Reference47 articles.
1. EmergencyNet: Efficient Aerial Image Classification for Drone-Based Emergency Monitoring Using Atrous Convolutional Feature Fusion
2. Experimental Results in Multi-UAV Coordination for Disaster Management and Civil Security Applications
3. A cooperative perception system for multiple UAVs: Application to automatic detection of forest fires
4. Wildfire Monitoring in Remote Areas using Autonomous Unmanned Aerial Vehicles
5. Fire detection using infrared images for UAV-based forest fire surveillance
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1. Drone Swarm Coordination Using Reinforcement Learning for Efficient Wildfires Fighting;SN Computer Science;2024-03-13
2. Robust Nonlinear Backstepping FTSMC of a Quadrotor UAV-Suspended Load System with Obstacle Avoidance and Swing Attenuation;2023 30th IEEE International Conference on Electronics, Circuits and Systems (ICECS);2023-12-04
3. Exploring unmanned aerial systems operations in wildfire management: data types, processing algorithms and navigation;International Journal of Remote Sensing;2023-09-17
4. Research on Autonomous and Collaborative Deployment of Massive Mobile Base Stations in High-Rise Building Fire Field;Sensors;2023-09-05
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