基于蚁群决策与滚动控制的多目的地航迹规划  

Multi-destination Path Planning Based on Ant Colony Decision-Making and Receding Control

作　　者：马晓毓 臧绍飞 马建伟[1] 张淼 MA Xiaoyu;ZANG Shaofei;MA Jianwei;ZHANG Miao(Henan University of Science and Technology Luoyang,471000,China)

机构地区：[1]河南科技大学,河南洛阳471000

出　　处：《电光与控制》2023年第8期26-32,共7页Electronics Optics & Control

基　　金：河南省高等学校重点科研项目(22A120005);河南省重点研发与推广专项(科技攻关)项目(222102210095)。

摘　　要：在战时无人机多目的地物资运输任务中,因其复杂的环境和多变的物资需求,存在目的地决策困难和航迹规划实时性要求高的问题。为了解决这一问题,提出一种基于蚁群决策与滚动控制的多目的地航迹规划方法。该方法借助蚁群算法中的寻优机制,建立以最小损耗为目标的多目的地决策函数;此外,采用基于扩充解的滚动时域控制(RHC_eS)法,采取边走边决策的策略,进行多目的地航迹规划;最后,为了验证该方法的有效性,在带有障碍物的多目的地环境下进行实验。结果表明,与其他方法相比,所提方法具有规划航路短、产生损耗小的优越性能。In wartime the multi-destination material transportation task of Unmanned Aerial Vehicle(UAV)has the problems of difficulty in determining the destination and high real-time requirements for path planning due to its complex environment and changeable material requirements.In order to solve the problems a multi-destination path planning method based on ant colony decision-making and receding control is proposed.This method establishes a multi-destination decision-making function with the minimum loss as the objective through the optimization mechanism of ant colony algorithm.In addition the Receding Horizon Control with extended Solution(RHC_eS)is adopted to carry out the multi-destination path planning by adopting the strategy of decision-making while moving at the same time.Finally in order to verify the effectiveness of the method experiments are carried out in a multi-destination environment with obstacles.The results show that compared with other methods,the proposed method has the advantages of shorter path and less loss.

关 键 词：智能决策 航迹规划 无人机 多目的地 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]