无人飞行器航迹规划的研究

发布时间：2018-06-21 15:23

本文选题：无人飞行器 + 航迹规划　；参考：《中北大学》2015年硕士论文

【摘要】：无人飞行器航迹规划是指在综合考虑无人飞行器的机动性能、燃料消耗，战场威胁等各种制约因素的基础上，为保证飞行器顺利完成任务而规划出一条满足要求的从起始点到目标点的最优航迹。航迹规划系统作为无人飞行器研究领域的重要组成部分，，是提高无人飞行器飞行能力和作战能力的重要保障。面对复杂多变的飞行环境和灵活多样的飞行任务，寻找更加有效的航迹规划方法成为航迹规划研究的重要内容。本课题主要围绕无人飞行器航迹规划的算法问题展开研究，首先介绍了航迹规划的研究背景以及国内外航迹规划技术的发展动态，分析并建立了合理的航迹规划问题模型，然后描述了无人飞行器自身机动性能约束，给出了在航迹规划时对战场威胁的处理方法并建立了相应的数学模型；其次，研究了目前在航迹规划中所应用的主流算法，然后根据战场已知威胁源构造Voronoi加权图，接着在Voronoi图的基础上，研究了全局航迹的优化方法。为了提高航迹规划问题最优解的质量及全局求解能力，针对蚁群算法存在的不足，提出了一种改进蚁群算法，采用全新的目标吸引策略、引入信息素增量调节因子并自适应调整信息素挥发系数来对基本蚁群算法进行了改进设计，通过对实验数据进行分析后发现，对于相同的规划问题，改进算法相比基本蚁群算法在规划时间上明显缩短，航迹长度值也显著减小；再次，由于战场环境是动态不确定的，无法准确地预知全局的威胁障碍信息，因此在参考航迹规划的基础上，研究无人飞行器实时航迹规划。针对出现突发威胁的情况阐述了实时重规划的原理，根据Voronoi图的局域动态特性提出了一种基于改进蚁群算法的实时重规划方法，并且对各种不同的实验设定情况分别进行了实例仿真，结果表明这种方法可以较好地解决突发威胁下的航迹规划问题，保证无人飞行器能够成功回避战场威胁，顺利完成任务。最后总结本文所做的研究工作及成果，并对需要展开深入的研究以及完善的内容进行了进一步探讨。
[Abstract]:Trajectory planning of unmanned aerial vehicles (UAV) is based on the comprehensive consideration of the maneuverability, fuel consumption, battlefield threat and other constraints of UAV. In order to ensure the successful completion of the mission, an optimal track from the starting point to the target point was designed. As an important part of unmanned aerial vehicle (UAV) research field, track planning system is an important guarantee to improve UAV's flight capability and combat capability. In the face of complex and changeable flight environment and flexible and diverse flight missions, finding more effective route planning methods has become an important content in the research of flight path planning. This topic mainly focuses on the algorithm of unmanned aerial vehicle (UAV) track planning. Firstly, the research background of track planning and the development trend of domestic and foreign track planning technology are introduced, and a reasonable trajectory planning model is established. Then, the maneuvering performance constraints of unmanned aerial vehicles are described, and the methods to deal with battlefield threats in track planning are given, and the corresponding mathematical models are established. Secondly, the mainstream algorithms used in track planning are studied. Then the Voronoi weighted diagram is constructed according to the known threat sources in the battlefield, and then the optimization method of the global track is studied based on the Voronoi diagram. In order to improve the quality of the optimal solution and the ability to solve the global problem, an improved ant colony algorithm (ACA) is proposed to improve the quality of the optimal solution and the ability to solve the problem globally, and an improved ant colony algorithm (ACA) is proposed, which adopts a new target attraction strategy. The pheromone increment regulation factor is introduced and the pheromone volatilization coefficient is adaptively adjusted to improve the design of the basic ant colony algorithm. After analyzing the experimental data, it is found that, for the same programming problem, Compared with the basic ant colony algorithm, the improved algorithm can significantly reduce the planning time and track length. Thirdly, because the battlefield environment is dynamic and uncertain, it is impossible to accurately predict the global threat obstacle information. Therefore, on the basis of reference track planning, the real-time track planning of unmanned aerial vehicles is studied. According to the local dynamic characteristics of Voronoi diagram, a real-time replanning method based on improved ant colony algorithm is proposed. The simulation results show that this method can solve the problem of trajectory planning under sudden threat and ensure that UAV can successfully avoid the threat of battlefield and complete the mission successfully. Finally, this paper summarizes the research work and results, and the need to carry out in-depth research and improve the content of further discussion.
【学位授予单位】：中北大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：V279

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