共查询到18条相似文献,搜索用时 218 毫秒
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针对三维空间双机协同定位问题,在无迹卡尔曼滤波的基础上,提出一种规划双机路径的方法。首先,利用双机探测得到的方位角和俯仰角信息,并结合无迹卡尔曼滤波算法估计目标的状态;在此基础上根据交互信息理论提出指标函数的概念,以指标函数最大为轨迹优化的最优性能指标,将问题转化为求双机控制量的最优解;最后,采用遗传算法求解双机的控制量,得到比较合理的双机飞行路径。仿真结果表明,通过最大化指标函数可以有效地规划双机路径,且具有更高的精度和速度。 相似文献
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航迹规划技术是无人机任务规划系统中重要的核心技术之一,无人机飞行空间广阔,需要一种快速搜索最佳路径的方法.首先在飞行区域中建立数字地图模型和防空威胁区模型,在满足无人机飞行约束条件的情况下,为无人机航迹规划提供一种遗传模拟退火算法,充分利用模拟退化算法的概率突跳特性和遗传算法强大的快速搜索能力.仿真结果表明,使用该算法无人机能够自动避开模拟数字地图的威胁区,搜索出一条安全有效航迹,并保证航线的完整性和最优性. 相似文献
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针对一类存在执行机构故障的分布式结构变体飞行器的控制分配问题,结合整数规划理论,提出一种基于布谷鸟搜索算法的容错控制方法。首先,设计虚拟控制指令,使得系统状态能够很好地跟踪参考模型;然后,将执行器概率性故障与饱和约束转换为整数规划问题中决策变量的约束,从而将执行器控制分配问题转化为一类整数规划问题;最后,采用改进的布谷鸟搜索算法进行求解,得到实际的执行器控制分配指令。仿真结果表明,在执行器存在概率性故障的情况下,该容错控制方法较无容错策略的情况能够有效提升系统的跟踪性能;与遗传算法相比,该算法得到的执行器控制分配结果更加精确。 相似文献
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随着无人机的广泛应用,其飞行能耗和计算能力面临着瓶颈问题,因此无人机路径规划研究越来越重要。很多情况下,无人机并不能提前获得目标点的确切位置和环境信息,往往无法规划出一条有效的飞行路径。针对这一问题,提出了基于导向强化Q学习的无人机路径规划方法,该方法利用接收信号强度定义回报值,并通过Q学习算法不断优化路径;提出"导向强化"的原则,加快了学习算法的收敛速度。仿真结果表明,该方法能够实现无人机的自主导航和快速路径规划,与传统算法相比,大大减少了迭代次数,能够获得更短的规划路径。 相似文献
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基于混沌蚁狮算法的无人机航迹规划 总被引:2,自引:0,他引:2
针对无人机在复杂战场环境下的最优航迹规划问题,提出了一种基于混沌蚁狮算法(CALO)的无人机航迹规划方法。对航迹规划问题进行了描述,建立了数学模型,将传统蚁狮算法中蚂蚁随机游走的行为和混沌算子结合,与蚁狮形成了全局、局部并行搜索模式,提高了算法寻找全局最优值的能力。在两种威胁环境下进行了仿真试验,搜索维度分别为10和20,并与经典人工蜂群算法(ABC)、传统蚁狮算法(ALO)、灰狼算法(GWO)进行对比,最后通过收敛曲线对仿真结果进行了统计分析。仿真结果验证了CALO算法在解决无人机航迹规划问题时的有效性和可行性。 相似文献
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针对传统的粒子群优化算法容易陷入局部最优解的问题,提出了一种自适应粒子群优化算法,在迭代寻优过程中自适应地调节惯性权重和2个学习因子的数值。建立了无人机在山区环境执行勘察任务的航迹规划环境模型,分析了无人机自身约束条件。设计了自适应粒子群优化算法的适应度函数和航迹规划算法流程。分别采用自适应粒子群优化算法和传统粒子群优化算法开展了无人机三维航迹规划仿真实验。仿真结果对比表明,所提出的自适应粒子群优化算法比传统粒子群优化算法具有更高的全局搜索能力和搜索精度。 相似文献
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Three-dimensional path planning for unmanned aerial vehicle based on interfered fluid dynamical system 总被引:1,自引:0,他引:1
This paper proposes a method for planning the three-dimensional path for low-flying unmanned aerial vehicle(UAV) in complex terrain based on interfered fluid dynamical system(IFDS) and the theory of obstacle avoidance by the flowing stream. With no requirement of solutions to fluid equations under complex boundary conditions, the proposed method is suitable for situations with complex terrain and different shapes of obstacles. Firstly, by transforming the mountains, radar and anti-aircraft fire in complex terrain into cylindrical, conical, spherical, parallelepiped obstacles and their combinations, the 3D low-flying path planning problem is turned into solving streamlines for obstacle avoidance by fluid flow. Secondly, on the basis of a unified mathematical expression of typical obstacle shapes including sphere, cylinder, cone and parallelepiped, the modulation matrix for interfered fluid dynamical system is constructed and 3D streamlines around a single obstacle are obtained. Solutions to streamlines with multiple obstacles are then derived using weighted average of the velocity field. Thirdly, extra control force method and virtual obstacle method are proposed to deal with the stagnation point and the case of obstacles’ overlapping respectively. Finally, taking path length and flight height as sub-goals, genetic algorithm(GA) is used to obtain optimal 3D path under the maneuverability constraints of the UAV. Simulation results show that the environmental modeling is simple and the path is smooth and suitable for UAV. Theoretical proof is also presented to show that the proposed method has no effect on the characteristics of fluid avoiding obstacles. 相似文献
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《中国航空学报》2021,34(9):199-209
In this paper, a bio-inspired path planning algorithm in 3D space is proposed. The algorithm imitates the basic mechanisms of plant growth, including phototropism, negative geotropism and branching. The algorithm proposed in this paper solves the dynamic obstacle avoidance path planning problem of Unmanned Aerial Vehicle (UAV) in the case of unknown environment maps. Compared with other path planning algorithms, the algorithm has the advantages of fast path planning speed and fewer route points, and can achieve the effect of low delay real-time path planning. The feasibility of the algorithm is verified in the Gazebo simulator based on the Robot Operating System (ROS) platform. Finally, an actual UAV autonomous obstacle avoidance path planning experimental platform is built, and a UAV obstacle avoidance path planning flight test is carried out based on this actual environment. 相似文献
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Study on UAV Path Planning Approach Based on Fuzzy Virtual Force 总被引:3,自引:2,他引:1
This article proposes a novel fuzzy virtual force (FVF) method for unmanned aerial vehicle (UAV) path planning in complicated environment. An integrated mathematical model of UAV path planning based on virtual force (VF) is constructed and the corresponding optimal solving method under the given indicators is presented. Specifically, a fixed step method is developed to reduce computational cost and the reachable condition of path planning is proved. The Bayesian belief network and fuzzy logic reasoning theories are applied to setting the path planning parameters adaptively, which can reflect the battlefield situation dynamically and precisely. A new way of combining threats is proposed to solve the local minima problem completely. Simulation results prove the feasibility and usefulness of using FVF for UAV path planning. Performance comparisons between the FVF method and the A* search algorithm demonstrate that the proposed approach is fast enough to meet the real-time requirements of the online path planning problems. 相似文献
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队形重构是集群无人机(UAV)控制的重要问题,指无人机按照要求安全、无碰撞地从一个队形变换到另一个队形,其难点在于快速规划最优安全轨迹并控制无人机进行轨迹姿态的高精度跟踪。针对集群无人机队形重构的上述问题,首先,基于CAPT(Concurrent Assignment and Planning of Trajectories)算法,解决了多无人机的目标分配和轨迹生成的实时性问题,实现了集群无人机的最优安全路径规划;其次,提出一种有限时间多变量积分滑模连续控制算法,解决了无人机轨迹姿态的高精度跟踪问题,并通过MATLAB仿真验证了该控制算法的有效性;最后,为了更加真实直观地演示无人机三维仿真效果,建立了基于Gazebo-ROS的无人机仿真平台,实现了12架四旋翼无人机队形重构"建模-仿真-可视化"的一体化仿真演示,验证了上述路径规划算法和轨迹姿态控制算法的有效性。 相似文献
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针对无人机三维在线航迹规划对算法速率、航迹最优性的需求,提出了基于改进ARA*算法的无人机在线航迹规划方法。首先,建立无人机三维航迹规划的数学模型;然后,提出了节点空间约简策略、局部启发项策略以提高算法收敛速率,并针对复杂规划环境提出了启发因子自适应递减策略。仿真结果表明,所提算法能够快速、稳定地生成首条可行航迹,并在剩余时间内不断提高航迹质量,可应用于不同类型的在线规划任务,动态地适应规划时间与航迹最优性的要求。 相似文献