Path Planning for a UAV Swarm Using Formation Teaching-Learning-Based Optimization

This work addresses the path planning problem for a group of unmanned aerial vehicles (UAVs) to maintain a desired formation during operation. Our approach formulates the problem as an optimization task by defining a set of fitness functions that not only ensure the formation but also include constr...

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Vydáno v:E3S web of conferences Ročník 626; s. 4001
Hlavní autoři: Hoang, Van Truong, Phung, Manh Duong
Médium: Journal Article Konferenční příspěvek
Jazyk:angličtina
Vydáno: Les Ulis EDP Sciences 01.01.2025
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ISSN:2267-1242, 2555-0403, 2267-1242
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Abstract This work addresses the path planning problem for a group of unmanned aerial vehicles (UAVs) to maintain a desired formation during operation. Our approach formulates the problem as an optimization task by defining a set of fitness functions that not only ensure the formation but also include constraints for optimal and safe UAV operation. To optimize the fitness function and obtain a suboptimal path, we employ the teaching-learning-based optimization algorithm and then further enhance it with mechanisms such as mutation, elite strategy, and multi-subject combination. A number of simulations and experiments have been conducted to evaluate the proposed method. The results demonstrate that the algorithm successfully generates valid paths for the UAVs to fly in a triangular formation for an inspection task.
AbstractList This work addresses the path planning problem for a group of unmanned aerial vehicles (UAVs) to maintain a desired formation during operation. Our approach formulates the problem as an optimization task by defining a set of fitness functions that not only ensure the formation but also include constraints for optimal and safe UAV operation. To optimize the fitness function and obtain a suboptimal path, we employ the teaching-learning-based optimization algorithm and then further enhance it with mechanisms such as mutation, elite strategy, and multi-subject combination. A number of simulations and experiments have been conducted to evaluate the proposed method. The results demonstrate that the algorithm successfully generates valid paths for the UAVs to fly in a triangular formation for an inspection task.
Author Hoang, Van Truong
Phung, Manh Duong
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SubjectTerms Algorithms
Machine learning
Optimization
Path planning
Unmanned aerial vehicles
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