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Published on: November 26, 2019
Multi UAV Coverage Path Planning in Urban Environments
Javier Muñoz1, Blanca López1, Fernando Quevedo1
1Robotics Lab, Universidad Carlos III de Madrid, Av. Madrid 30, 28911 Leganés, Spain.
This study introduces novel algorithms for Unmanned Aerial Vehicle (UAV) coverage path planning (CPP) in urban areas. The developed methods ensure efficient, collision-free flight paths for UAV formations, enhancing safety and mission success.
Area of Science:
- Robotics and Automation
- Aerospace Engineering
- Computer Science
Background:
- Coverage Path Planning (CPP) is crucial for Unmanned Aerial Vehicle (UAV) applications like surveillance and mapping.
- Urban environments present significant challenges for UAV navigation due to clutter and obstacles.
- Existing CPP algorithms often lack robust collision avoidance for multi-UAV systems in complex settings.
Purpose of the Study:
- To design efficient, collision-avoidance capable coverage path planning algorithms for single or multi-UAV systems.
- To enable UAVs to safely and smoothly cover target zones or survey predefined viewpoints in cluttered urban environments.
- To develop scalable algorithms adaptable to varying numbers of UAVs and formations.
Main Methods:
- Development of two distinct CPP algorithms: one utilizing a boustrophedon pattern for area coverage and another for viewpoint-based path planning.
- Implementation of a deformable triangular leader-follower formation for multi-UAV coordination, including a virtual leader strategy for even UAV numbers.
- Integration of the Fast Marching Square algorithm for robust collision avoidance capabilities.
- Simulation-based testing in diverse, cluttered urban environments to validate algorithm performance.
Main Results:
- Both developed algorithms successfully generated safe and smooth paths for UAV formations in simulated urban environments.
- The algorithms demonstrated scalability for a variable number of UAVs operating in coordinated formations.
- Collision avoidance was effectively managed, ensuring operational safety within complex, cluttered settings.
- The viewpoint-based algorithm ensured UAVs passed smoothly over designated objectives.
Conclusions:
- The proposed CPP algorithms offer effective solutions for UAV navigation and coverage in challenging urban landscapes.
- The integration of advanced collision avoidance and formation strategies enhances the reliability and safety of multi-UAV operations.
- These algorithms represent a significant advancement in enabling proficient UAV deployment for various urban applications.
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