Optimal Path Planning for Multi-UAV Based on Pseudo-spectral Method

Jin, Pengfei; Cui, Yu; Wang, Aihua; Hou, Zhen-Qian; Yichong, Wang

doi:10.1109/icbaie49996.2020.00094

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…Pengfei et al [149] proposed an optimal trajectory planning method for multiple UAVs based on the pseudospectral method. This method uses the pseudospectral method to transform the optimal control problem with complex constraints into a nonlinear programming problem; at the same time, it uses the distributed solution and the Nash optimal coordination strategy to solve the multi-UAV trajectory planning problem under complex and multi-constrained conditions.…”

Section: Mathematical Optimization Algorithmmentioning

confidence: 99%

UAV Formation Trajectory Planning Algorithms: A Review

Yang

Xiong

Yan

2023

Drones

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With the continuous development of UAV technology and swarm intelligence technology, the UAV formation cooperative mission has attracted wide attention because of its remarkable function and flexibility to complete complex and changeable tasks, such as search and rescue, resource exploration, reconnaissance and surveillance. The collaborative trajectory planning of UAV formation is a key part of the task execution. This paper attempts to provide a comprehensive review of UAV formation trajectory planning algorithms. Firstly, from the perspective of global planning and local planning, a simple framework of the UAV formation trajectory planning algorithm is proposed, which is the basis of comprehensive classification of different types of algorithms. According to the proposed framework, a classification method of existing UAV formation trajectory planning algorithms is proposed, and then, different types of algorithms are described and analyzed statistically. Finally, the challenges and future research directions of the UAV formation trajectory planning algorithm are summarized and prospected according to the actual requirements. It provides reference information for researchers and workers engaged in the formation flight of UAVs.

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Section: Mathematical Optimization Algorithmmentioning

confidence: 99%