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WANG H F . Development of high performance collaborative combat UAVs [J ] . Acta Aeronautica et Astronautica Sinica , 2024 , 45 ( 17 ): 530304 . (in Chinese)

曾照洋 , 彭文胜 , 李云凯 , 等 . 智能无人机集群可靠性技术内涵、发展及挑战 [J ] . 兵工学报 , 2025 , 46 ( 3 ): 240322 . DOI: 10.12382/bgxb.2024.0322 http://doi.org/10.12382/bgxb.2024.0322 随着无人机相关技术的快速发展,智能无人机集群得到越来越多的研究。智能无人机集群应用自然界集群组织算法模型,并结合其他智能技术,形成高级群体智能行为,具有传统单人工智能体无法比拟的优势,但是可靠性问题也是制约其面向大规模应用的一个重要因素。系统分析智能无人机集群的概念、特征及技术发展路径,基于智能无人机集群的应用场景、应用模式及行为过程,探讨智能无人机集群的可靠性内涵,构建无人机集群可靠性技术框架,并结合智能无人机集群的技术特征和应用需求,给出智能无人机集群可靠性技术发展的技术途径与建议。最终在“1个核心,2种能力,N个基础”的可靠性内涵下,提出由可靠性指标、可靠性研制验证以及可靠性维持保障技术组成的智能UAVS可靠性技术框架。

ZENG Z Y , PENG W S , LI Y K , et al. Connotation, development and challenges of reliability technology of intelligent UAV swarm [J ] . Acta Armamentarii , 2025 , 46 ( 3 ): 240322 . (in Chinese)

陈丽芳 , 杨火根 , 陈智超 , 等 . B样条技术与遗传算法融合的全局路径规划 [J ] . 浙江大学学报(工学版) , 2024 , 58 ( 12 ): 2520 - 2530 .

CHEN L F , YANG H G , CHEN Z C , et al. Global path planning with integration of B-spline technique and genetic algorithm [J ] . Journal of Zhejiang University (Engineering Science) , 2024 , 58 ( 12 ): 2520 - 2530 . (in Chinese)

王东振 , 张岳 , 赵宇 , 等 . 基于RRT-Dubins的无人机航迹优化方法 [J ] . 兵工学报 , 2024 , 45 ( 8 ): 2761 - 2773 . DOI: 10.12382/bgxb.2023.0611 http://doi.org/10.12382/bgxb.2023.0611 针对多障碍物环境下考虑无人机(Unmanned Aerial Vehicle,UAV)始末位姿、转弯半径和航迹长度的1阶光滑约束的UAV航迹规划问题,提出一种基于快速搜索随机树(Rapidly-exploring Random Trees,RRT)算法和Dubins曲线以局部最优逼近全局最优的UAV航迹优化方法。利用RRT算法和基于贪心算法的剪枝优化方法,在二维任务空间中规划出满足避障要求的可行离散航路点。采用多条Dubins曲线平滑连接航路点,根据UAV始末位姿确定首尾曲线端点,基于UAV性能、障碍物和飞行参数的约束关系,建立多约束的航迹优化数学模型。通过粒子群优化算法确定曲线类型,同时优化曲线连接处位姿和曲线半径,获得最短航迹。仿真结果表明:所提方法得到的航迹与其他方法相比,在不同障碍物数量和始末位姿的多种场景中,平均长度缩短了11.48%,在避开障碍物的同时,满足UAV动力学约束。

WANG D Z , ZHANG Y , ZHAO Y , et al. A UAV trajectory optimization method based on RRT-Dubins [J ] . Acta Armamentarii , 2024 , 45 ( 8 ): 2761 - 2773 . (in Chinese) DOI: 10.12382/bgxb.2023.0611 http://doi.org/10.12382/bgxb.2023.0611 A unmanned aerial vehicle (UAV) trajectory optimization method based on the rapidly-exploring random trees (RRT) algorithm and Dubins curves is proposed to address the problem of UAV trajectory planning in multi-obstacle environments. The initial and final poses, turning radius, and trajectory length, and first-order smoothness constraint of UAV are considered in the trajectory planning. The RRT algorithm and a pruning optimization method based on a greedy algorithm are utilized to plan the feasible discrete waypoints that satisfy the obstacle avoidance requirements in a two-dimensional task space. Multiple Dubins curves are employed to smoothly connect the waypoints. A multi-constraint trajectory optimization mathematical model is established based on the UAV's initial and final poses, and the constraints related to the UAV's performance and obstacles. The particle swarm optimization (PSO) algorithm is employed to determine the curve types and optimize the poses at the curve connections and the curve radii, thereby obtaining the shortest trajectory. Simulated results demonstrate that the proposed method reduces the average trajectory length by 11.48% in various scenarios with different numbers of obstacles and varying initial and final positions, while satisfying the UAV's kinematic constraints and avoiding obstacles compared to other methods.

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GENG Z X , GUANG X , CHEN J Y , et al. Urban UAV route planning based on chaotic PSO algorithm [J ] . Journal of Xihua University(Natural Science Edition) , 2024 , 43 ( 6 ): 1 - 7 . (in Chinese)

习凤 , 林逢春 . 结合模拟退火算法与遗传算法的动态协同路径规划研究 [J ] . 舰船科学技术 , 2024 , 46 ( 19 ): 161 - 164 .

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朱瑾 , 黄琦 . 路网资源分配下自动化码头水平运输调度与路径规划 [J ] . 吉林大学学报(工学版) , 2024 , 54 ( 8 ): 2245 - 2255 .

ZHU J , HUANG Q . Horizontal transport scheduling and path planning for automated terminals under roadnetwork resource allocation [J ] . Journal of Jilin University (Engineering Edition) , 2024 , 54 ( 8 ): 2245 - 2255 . (in Chinese)

王康 , 司鹏 , 陈莉 , 等 . 基于改进沙猫群算法的无人机三维航迹规划 [J ] . 兵工学报 , 2023 , 44 ( 11 ): 3382 - 3393 . DOI: 10.12382/bgxb.2023.0763 http://doi.org/10.12382/bgxb.2023.0763 针对传统沙猫群(SCSO)算法全局搜索能力不足、易陷入局部最优等问题,提出一种改进沙猫群(LVSCSO)算法。该算法引入非线性调整机制,更好地体现出SCSO算法的搜寻和攻击过程;同时引入自适应莱维飞行机制,有效提高了算法的全局搜索能力和跳出局部最优的能力。采用栅格法构建无人机野外环境模型和复杂城市环境模型,以综合航迹长度、飞行高度和飞行转角的适应度函数为衡量指标,进行了算法的仿真验证。研究结果表明:在野外环境模型下,相较于传统SCSO算法和粒子群优化算法,该改进算法分别提升56.40%和22.06%;在复杂城市环境模型下,相较于传统SCSO算法和粒子群优化算法,该改进算法分别提升了56.33%和61.80%;新的LVSCSO算法在航迹规划上具有有效性和优越性。

WANG K , SI P , CHEN L , et al. 3D path planning of unmanned aerial vehicle based on enhanced sand cat swarm optimization algorithm [J ] . Acta Armamentarii , 2023 , 44 ( 11 ): 3382 - 3393 . (in Chinese) DOI: 10.12382/bgxb.2023.0763 http://doi.org/10.12382/bgxb.2023.0763 In response to the limitations of the traditional Sand Cat Swarm Optimization(SCSO) algorithm, including inadequate global search capability and susceptibility to local optima, an improved Sand Cat Swarm Optimization (LVSCSO) algorithm is proposed. The proposed algorithm introduces a nonlinear adjustment mechanism to better encapsulate the search and attack processes inherent in SCSO algorithm. Moreover, an adaptive Levy flight mechanism is incorporated to effectively enhance the algorithm’s global search capability and capacity to escape local optima. A grid-based approach is used to establish the wilderness and complex urban environment models for unmanned aerial vehicles(UAVs). A composite fitness function, considering the factors such as path length, flight altitude, and flight angles, serves as the evaluation metric. The algorithm is validated through simulation.The results show that, in the wilderness environment model, the improved algorithm achieves the enhancements of 56.40% and 22.06% over the traditional SCSO algorithm and the particle swarm optimization algorithm, respectively. In the complex urban environment model, the improvements are 56.33% and 61.80% compared to the traditional SCSO algorithm and the particle swarm algorithm, respectively. These findings highlight the efficacy and superiority of the improved SCSO algorithm in the context of path planning.

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吴亚中 , 陈璐 , 马强 , 等 . 多策略增强的蜣螂优化算法及其工程应用 [J ] . 华中科技大学学报(自然科学版) , 2025 , 53 ( 2 ): 95 - 103 .

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隋东 , 杨振宇 , 丁松滨 , 等 . 基于EMSDBO算法的无人机三维航迹规划 [J ] . 系统工程与电子技术 , 2024 , 46 ( 5 ): 1756 - 1766 . DOI: 10.12305/j.issn.1001-506X.2024.05.28 http://doi.org/10.12305/j.issn.1001-506X.2024.05.28 针对无人机(unmanned aerial vehicle, UAV)三维航迹规划问题, 提出一种增强型多策略蜣螂算法的UAV航迹规划方法。首先, 将飞行接近率和响应时间的动态约束添加到威胁成本代价中, 并考虑UAV转弯性能的影响, 建立三维任务空间模型与航迹代价函数。其次, 在蜣螂算法中引入偏移估计策略、变螺旋搜索策略、准反向学习策略和逐维变异策略, 提高算法的全局寻优能力和收敛速度。最后, 给出了改进算法在三维环境下航迹规划的仿真结果。结果表明: 综合考虑UAV机动性能和转弯性能, 规划出的路径可以更加安全有效地避开危险源。相比其他算法, 改进算法的寻优能力更好, 规划的航迹质量更优。

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