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Path Planning and Collision Risk Management Strategy for Multi-UAV Systems in 3D Environments
by
Garrido, Santiago
, López, Blanca
, Monje, Concepción A.
, Quevedo, Fernando
, Muñoz, Javier
, Moreno, Luis E.
in
autonomous vehicle
/ collision avoidance
/ fast marching
/ multi-UAV systems
/ path planning
/ velocity control
2021
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Path Planning and Collision Risk Management Strategy for Multi-UAV Systems in 3D Environments
by
Garrido, Santiago
, López, Blanca
, Monje, Concepción A.
, Quevedo, Fernando
, Muñoz, Javier
, Moreno, Luis E.
in
autonomous vehicle
/ collision avoidance
/ fast marching
/ multi-UAV systems
/ path planning
/ velocity control
2021
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Do you wish to request the book?
Path Planning and Collision Risk Management Strategy for Multi-UAV Systems in 3D Environments
by
Garrido, Santiago
, López, Blanca
, Monje, Concepción A.
, Quevedo, Fernando
, Muñoz, Javier
, Moreno, Luis E.
in
autonomous vehicle
/ collision avoidance
/ fast marching
/ multi-UAV systems
/ path planning
/ velocity control
2021
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Path Planning and Collision Risk Management Strategy for Multi-UAV Systems in 3D Environments
Journal Article
Path Planning and Collision Risk Management Strategy for Multi-UAV Systems in 3D Environments
2021
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Overview
Multi-UAV systems are attracting, especially in the last decade, the attention of researchers and companies of very different fields due to the great interest in developing systems capable of operating in a coordinated manner in complex scenarios and to cover and speed up applications that can be dangerous or tedious for people: search and rescue tasks, inspection of facilities, delivery of goods, surveillance, etc. Inspired by these needs, this work aims to design, implement and analyze a trajectory planning and collision avoidance strategy for multi-UAV systems in 3D environments. For this purpose, a study of the existing techniques for both problems is carried out and an innovative strategy based on Fast Marching Square—for the planning phase—and a simple priority-based speed control—as the method for conflict resolution—is proposed, together with prevention measures designed to try to limit and reduce the greatest number of conflicting situations that may occur between vehicles while they carry out their missions in a simulated 3D urban environment. The performance of the algorithm is evaluated successfully on the basis of certain conveniently chosen statistical measures that are collected throughout the simulation runs.
Publisher
MDPI,MDPI AG
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