A novel UAV path planning approach: Heuristic crossing search and rescue optimization algorithm

Unmanned aerial vehicle (UAV) path planning plays an important role in the flight process of an UAV, which needs an effective algorithm to deal with UAV path planning problem. The search and rescue optimization algorithm (SAR) is easy to implement and has the characteristics of flexible, but it has...

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Vydáno v:Expert systems with applications Ročník 215; s. 119243
Hlavní autoři: Zhang, Chaoqun, Zhou, Wenjuan, Qin, Weidong, Tang, Weidong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.04.2023
Témata:
Heuristic crossing search and rescue optimization algorithm
Path adjustment
Path planning
Search and rescue optimization algorithm
Unmanned aerial vehicle
Path planning
Search and rescue optimization algorithm
Path adjustment
Unmanned aerial vehicle
Heuristic crossing search and rescue optimization algorithm
ISSN:0957-4174, 1873-6793
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Shrnutí:Unmanned aerial vehicle (UAV) path planning plays an important role in the flight process of an UAV, which needs an effective algorithm to deal with UAV path planning problem. The search and rescue optimization algorithm (SAR) is easy to implement and has the characteristics of flexible, but it has slow convergence speed and has not been applied to UAV path planning. To address these problems, a heuristic crossing search and rescue optimization algorithm (HC-SAR) is proposed. HC-SAR combines a heuristic crossover strategy with the basic SAR to improve the convergence speed and maintain the population diversity in the optimization process. Furthermore, a real-time path adjustment strategy is proposed to straighten the UAV flight path. In addition, cubic B-spline interpolation is used to smooth the generated path. Comprehensive experiments including two-dimensional and three-dimensional environments for different threat zone are conducted to validate the performance of HC-SAR. The results show that HC-SAR has a high convergence speed and can successfully obtain a safe and efficient path, and it significantly outperforms SAR, differential evolution (DE), ant lion optimizer (ALO), squirrel search algorithm (SSA) and salp swarm algorithm (SSA) in all the cases. These results suggest that the proposed algorithm can effectively serve as an alternative for solving UAV path planning problem. •A hybrid algorithm named HC-SAR is proposed for UAV path planning.•A heuristic crossover strategy is combined with SAR to greatly improve SAR.•A real-time path adjustment strategy is proposed to straighten the UAV flight path.•HC-SAR outperforms the competitors in convergence speed and solution quality.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2022.119243