无人机航迹规划算法的研究
发布时间：2018-12-14 15:32
【摘要】：随着信息技术的日益革新,航空技术得到了迅猛的发展,复杂多变的飞行环境对无人机的机动性提出了巨大挑战。航迹规划是实现无人机自主飞行的关键技术,其所采用的规划算法是必要的技术保障,所以对航迹规划算法的研究在理论和实际应用方面都有很重要的意义。本文围绕航迹规划算法展开研究,给出了相应的航迹规划策略,主要研究内容如下:(1)针对航迹规划中所需要满足的约束条件,建立了无人机机动性约束模型。根据任务需求,对飞行环境中的静态威胁源(如静态雷达等)进行了深入分析并建立相应模型。同时也构建了综合代价函数模型,这些模型的建立为研究航迹规划奠定了基础。(2)对静态环境下的航迹规划问题,采用了改进后的遗传算法。设计了一种基于航向变化量的实数编码方式,对航向变化量进行编码构造个体,再根据个体编码向量构造临时路径。通过设计的编码方式和相应的遗传操作来进行静态规划,并对算法改进前后的仿真结果进行了对比分析。(3)对动态环境下的航迹规划问题,提出了基于交互式多模型算法和模型预测控制算法的融合算法。根据运动目标的当前位置信息,采用交互式多模型算法预测其轨迹,实现对移动障碍物的提前避规。同时,利用转换测量卡尔曼滤波将非线性问题转化为线性问题来解决。综合考虑静态、动态等多种威胁约束同时存在的飞行环境,采用融合算法进行仿真,对算法的实时性和有效性进行了验证。(4)针对三维空间航迹规划问题,提出了一种基于改进蚁群算法的航迹规划方法。利用数字地图技术建立了三维地形模拟图,在考虑威胁代价、航程代价和高度代价约束条件下,构建了综合代价目标函数。在综合考虑可选节点与目标点之间距离的基础上,重新设定了状态转移概率。此外,结合分类思想在信息素浓度更新时,在一定范围内对信息素残留因子进行设定,提高了搜索时路径的选择性,避免产生“早熟”现象,同时改善了搜索时间长、容易陷入局部最优解等问题。结合算法的理论分析进行仿真,结果表明三维空间中利用改进后的蚁群算法进行航迹规划可以得到期望航线。
[Abstract]:With the development of information technology, aeronautical technology has been developed rapidly, and the complex and changeable flight environment has posed a great challenge to the maneuverability of UAVs. Track planning is the key technology to realize autonomous flight of UAV, and the planning algorithm is the necessary technical guarantee. Therefore, the research of track planning algorithm is of great significance in both theory and practical application. In this paper, the algorithm of track planning is studied, and the corresponding route planning strategies are given. The main contents are as follows: (1) aiming at the constraints that need to be met in track planning, the maneuverability constraint model of UAV is established. According to the mission requirements, the static threat sources (such as static radar) in flight environment are analyzed and the corresponding models are established. At the same time, the synthetic cost function model is constructed, which lays a foundation for the research of track planning. (2) the improved genetic algorithm is used to solve the problem of track planning in static environment. A real number coding method based on course variable is designed to construct the individual and construct the temporary path according to the individual coding vector. The static programming is carried out by the coding method designed and the corresponding genetic operation, and the simulation results before and after the improvement of the algorithm are compared and analyzed. (3) the trajectory planning problem in dynamic environment is discussed. A fusion algorithm based on interactive multi-model algorithm and model predictive control algorithm is proposed. Based on the current position information of moving objects, an interactive multi-model algorithm is used to predict the trajectory of moving obstacles. At the same time, the nonlinear problem is transformed into a linear problem by using the transform measurement Kalman filter. Considering the flight environment with static and dynamic threat constraints, the fusion algorithm is used to simulate the real-time and validity of the algorithm. (4) aiming at the problem of 3D flight path planning, A route planning method based on improved ant colony algorithm is proposed. The 3D terrain simulation map is established by using digital map technology. The objective function of synthetic cost is constructed under the constraints of threat cost, voyage cost and height cost. On the basis of considering the distance between the optional node and the target point, the state transition probability is reset. In addition, when the pheromone concentration is updated according to the classification idea, the pheromone residue factor is set within a certain range, which improves the selectivity of the search path, avoids the phenomenon of "precocity" and improves the long search time. It is easy to fall into local optimal solutions and other problems. Based on the theoretical analysis of the algorithm, the simulation results show that the improved ant colony algorithm can get the desired route in 3D space.
【学位授予单位】：杭州电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：V279;V249;TP18
[Abstract]:With the development of information technology, aeronautical technology has been developed rapidly, and the complex and changeable flight environment has posed a great challenge to the maneuverability of UAVs. Track planning is the key technology to realize autonomous flight of UAV, and the planning algorithm is the necessary technical guarantee. Therefore, the research of track planning algorithm is of great significance in both theory and practical application. In this paper, the algorithm of track planning is studied, and the corresponding route planning strategies are given. The main contents are as follows: (1) aiming at the constraints that need to be met in track planning, the maneuverability constraint model of UAV is established. According to the mission requirements, the static threat sources (such as static radar) in flight environment are analyzed and the corresponding models are established. At the same time, the synthetic cost function model is constructed, which lays a foundation for the research of track planning. (2) the improved genetic algorithm is used to solve the problem of track planning in static environment. A real number coding method based on course variable is designed to construct the individual and construct the temporary path according to the individual coding vector. The static programming is carried out by the coding method designed and the corresponding genetic operation, and the simulation results before and after the improvement of the algorithm are compared and analyzed. (3) the trajectory planning problem in dynamic environment is discussed. A fusion algorithm based on interactive multi-model algorithm and model predictive control algorithm is proposed. Based on the current position information of moving objects, an interactive multi-model algorithm is used to predict the trajectory of moving obstacles. At the same time, the nonlinear problem is transformed into a linear problem by using the transform measurement Kalman filter. Considering the flight environment with static and dynamic threat constraints, the fusion algorithm is used to simulate the real-time and validity of the algorithm. (4) aiming at the problem of 3D flight path planning, A route planning method based on improved ant colony algorithm is proposed. The 3D terrain simulation map is established by using digital map technology. The objective function of synthetic cost is constructed under the constraints of threat cost, voyage cost and height cost. On the basis of considering the distance between the optional node and the target point, the state transition probability is reset. In addition, when the pheromone concentration is updated according to the classification idea, the pheromone residue factor is set within a certain range, which improves the selectivity of the search path, avoids the phenomenon of "precocity" and improves the long search time. It is easy to fall into local optimal solutions and other problems. Based on the theoretical analysis of the algorithm, the simulation results show that the improved ant colony algorithm can get the desired route in 3D space.
【学位授予单位】：杭州电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：V279;V249;TP18
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6 李t，
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