计算机科学
路径(计算)
运动规划
算法
人工智能
机器人
计算机网络
作者
Xinxin Zhao,Shukun Cao,Wenwen Zhang,Guo Zhao,Mengjie Xing
摘要
In the UAV path planning problem, traditional algorithms have shortcomings such as computational complexity and convergence. WOA algorithm is concise and easy to implement, and has loose requirements on objective function conditions and less parameter control, etc. However, its lack of adaptability and difference limits its performance in complex optimization problems. In this study, a nonlinear convergence factor and an adaptive weight strategy were introduced. In the simulation verification, multiple constraints were considered and added into the objective function as a penalty term to build a route planning model under the UAV flight mission scenario, and the improved WOA algorithm was used to solve the optimal path. Through simulation verification, the results proved that the improved WOA algorithm was efficient and practical. The final simulation verifies the efficiency and practicability of improved WOA algorithm.
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