2020
DOI: 10.3390/s20030642
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3D Trajectory Planning Method for UAVs Swarm in Building Emergencies

Abstract: The development in Multi-Robot Systems (MRS) has become one of the most exploited fields of research in robotics in recent years. This is due to the robustness and versatility they present to effectively undertake a set of tasks autonomously. One of the essential elements for several vehicles, in this case, Unmanned Aerial Vehicles (UAVs), to perform tasks autonomously and cooperatively is trajectory planning, which is necessary to guarantee the safe and collision-free movement of the different vehicles. This … Show more

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Cited by 48 publications
(37 citation statements)
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References 33 publications
(34 reference statements)
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“…A multi-trajectory planning scheme for the UAV cluster based on a 3D probabilistic road map (PRM) is mentioned. The UAV swarm can reach different places (marked and unmarked) in different situations and support emergency conditions in the city environment [60]. For the UAV path planning in the threat and confrontation area is a non-linear optimization problem with multiple static and dynamic constraints , through a multi-drones collaborative path planning method on 3D rugged terrain multi-swarm fruit fly optimization algorithm (MSFOA), which solves the shortcomings of the original algorithm that the global convergence speed is too slow and the local optimization [61].…”
Section: Figure 6 Mainstream Path Planning Algorithmsmentioning
confidence: 99%
“…A multi-trajectory planning scheme for the UAV cluster based on a 3D probabilistic road map (PRM) is mentioned. The UAV swarm can reach different places (marked and unmarked) in different situations and support emergency conditions in the city environment [60]. For the UAV path planning in the threat and confrontation area is a non-linear optimization problem with multiple static and dynamic constraints , through a multi-drones collaborative path planning method on 3D rugged terrain multi-swarm fruit fly optimization algorithm (MSFOA), which solves the shortcomings of the original algorithm that the global convergence speed is too slow and the local optimization [61].…”
Section: Figure 6 Mainstream Path Planning Algorithmsmentioning
confidence: 99%
“…In this context, Unmanned Aerial Vehicles (UAVs) arose as a prominent solution to automate this process in a cost-effectively way. In addition, UAVs have positioned at the forefront of different application fields, such as infrastructure inspection [ 1 , 2 ], search and rescue [ 3 , 4 ], delivery [ 5 , 6 ], among others. In the scenario of large structures’ inspections, the UAV may help decrease the mission’s complexity, such as data gathering and geometry land specifications due to its maneuvering flexibility, high versatility, and the possibility of attaching new technologies into it [ 2 ].…”
Section: Introductionmentioning
confidence: 99%
“…Swarms of drones have demand in vast and diverse application areas for instance in the military, commercial use, search and rescue, monitoring traffic, threat detection especially at borders, and atmospheric research purposes [4], [5]. Due to the ability to work in a collaborative manner in a 3dimensional space, research on optimal navigation of swarms is gaining even more attention in the research community [6].…”
Section: Introductionmentioning
confidence: 99%