[1]QIN Dongyan,YAN Xiaohui,SHAO Guiwei,et al.Event-triggered gray wolf optimization for quadrotor unmanned aerial vehicle three-dimensional trajectory planning[J].CAAI Transactions on Intelligent Systems,2025,20(3):699-706.[doi:10.11992/tis.202406013]
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Event-triggered gray wolf optimization for quadrotor unmanned aerial vehicle three-dimensional trajectory planning
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
20
Number of periods:
2025 3
Page number:
699-706
Column:
学术论文—智能系统
Public date:
2025-05-05
- Title:
- Event-triggered gray wolf optimization for quadrotor unmanned aerial vehicle three-dimensional trajectory planning
- Keywords:
- improved GWO algorithm; event-triggered; 3D path planning; spherical vector; adaptive weight; nonlinear convergence factor; velocity pausing; quadrotor unmanned aerial vehicle
- CLC:
- TP242
- DOI:
- 10.11992/tis.202406013
- Abstract:
- An improved event-triggered gray wolf optimization algorithm (ETGWO) is proposed for the 3D path planning of quadrotor unmanned aerial vehicles in complex environments. First, the search space and search capabilities are reduced and improved, respectively, by introducing spherical vectors to characterize flight path generation. Second, the adaptive weights are designed to dynamically adjust the fitness function of the flight trajectory cost, thereby improving the efficiency and accuracy of path planning. Based on the gray wolf optimization (GWO) algorithm, a nonlinear convergence factor is selected to enhance the robustness of the algorithm. Additionally, to better balance the global and local search capabilities, the position update strategy of the gray wolf individuals is developed based on the update velocity, which is integrated with the event-triggered mechanism. Finally, simulation and comparative experiments are performed to confirm the superior planning performance of ETGWO compared with those of other algorithms.
- References:
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1900-01-01