A Multi-UAV System for Exploration and Target Finding in Cluttered and GPS-Denied Environments
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Author(s)
Zhu, Xiaolong
Gonzalez, Felipe
Vanegas, Fernando
Sanderson, Conrad
Griffith University Author(s)
Year published
2021
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The use of multi-rotor Unmanned Aerial Vehicles (UAVs) for Search and Rescue (SAR) and Remote Sensing is rapidly increasing. Multi-rotor UAVs, however, have limited endurance. The range of UAV applications can be widened if teams of multiple UAVs are used. We propose a framework for a team of UAVs to cooperatively explore and find a target in complex GPS-denied environments with obstacles. The team of UAVs autonomously navigates, explores, detects, and finds the target in a cluttered environment with a known map. Examples of such environments include indoor scenarios, urban or natural canyons, caves, and tunnels, where the ...
View more >The use of multi-rotor Unmanned Aerial Vehicles (UAVs) for Search and Rescue (SAR) and Remote Sensing is rapidly increasing. Multi-rotor UAVs, however, have limited endurance. The range of UAV applications can be widened if teams of multiple UAVs are used. We propose a framework for a team of UAVs to cooperatively explore and find a target in complex GPS-denied environments with obstacles. The team of UAVs autonomously navigates, explores, detects, and finds the target in a cluttered environment with a known map. Examples of such environments include indoor scenarios, urban or natural canyons, caves, and tunnels, where the GPS signal is limited or blocked. The framework is based on a probabilistic Decentralised Partially Observable Markov Decision Processes (Dec-POMDP) which accounts for the uncertainties in sensing and the environment. The team can cooperate efficiently, with each UAV sharing only limited processed observations and their locations during the mission. The system is simulated using the Robotic Operating System (ROS) and Gazebo. Performance of the system with an increasing number of UAVs in several indoor scenarios with obstacles is tested. Results indicate that the proposed multi-UAV system has improvements in terms of time-cost, the proportion of search area surveyed, and successful rates for search and rescue missions.
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View more >The use of multi-rotor Unmanned Aerial Vehicles (UAVs) for Search and Rescue (SAR) and Remote Sensing is rapidly increasing. Multi-rotor UAVs, however, have limited endurance. The range of UAV applications can be widened if teams of multiple UAVs are used. We propose a framework for a team of UAVs to cooperatively explore and find a target in complex GPS-denied environments with obstacles. The team of UAVs autonomously navigates, explores, detects, and finds the target in a cluttered environment with a known map. Examples of such environments include indoor scenarios, urban or natural canyons, caves, and tunnels, where the GPS signal is limited or blocked. The framework is based on a probabilistic Decentralised Partially Observable Markov Decision Processes (Dec-POMDP) which accounts for the uncertainties in sensing and the environment. The team can cooperate efficiently, with each UAV sharing only limited processed observations and their locations during the mission. The system is simulated using the Robotic Operating System (ROS) and Gazebo. Performance of the system with an increasing number of UAVs in several indoor scenarios with obstacles is tested. Results indicate that the proposed multi-UAV system has improvements in terms of time-cost, the proportion of search area surveyed, and successful rates for search and rescue missions.
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Conference Title
2021 International Conference on Unmanned Aircraft Systems (ICUAS)
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Copyright Statement
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Subject
Applied mathematics
Numerical and computational mathematics
Distributed computing and systems software
Aerospace engineering
Communications engineering