飞行器避障与航迹规划研究

发布时间：2018-06-26 21:54

本文选题：无人机 + 航迹规划　；参考：《北京理工大学》2015年硕士论文

【摘要】：航迹规划是指在一些特定的约束条件下,为飞行器寻找从起始点到目标点满足某些性能指标的最优飞行航迹。航迹规划是实现飞行器自主智能的一项关键技术,无论在理论还是实际应用上都具有重大意义。论文围绕无人机航迹规划技术,主要对以下内容进行研究:(1)航迹规划空间的建模;(2)航迹规划算法;(3)威胁回避技术研究。首先,本文介绍了航迹规划的研究背景,并对国内外研究现状以及发展趋势进行了综述。然后,分别介绍了无人机航迹规划的基础,包括航迹表示、环境模型的建立,如:数字地形和常见威胁模型、无人机运动学性能约束模型以及航迹评价。其次,对典型航迹规划算法进行研究对比,重点介绍了稀疏A*算法和基于遗传算法的航迹规划并仿真验证。在此基础上,论文提出了采用最小二叉堆数据结构和变步长方案的改进A*算法。针对遗传算法收敛慢和早熟特性,提出了产生优秀个体的A搜索方案,并通过仿真结果对比分析。再次,对三维航迹避障方法进行研究,提出了基于几何学的三维避障方法并仿真分析验证算法的可行性。
[Abstract]:Track planning refers to finding the optimal flight path for the aircraft from the starting point to the target point under some specific constraints. Track planning is a key technology to realize autonomous intelligence of aircraft, which is of great significance both in theory and in practice. This paper focuses on the technology of UAV track planning. The main contents are as follows: (1) the modeling of track planning space; (2) the algorithm of route planning; (3) the research of threat avoidance technology. Firstly, this paper introduces the research background of route planning, and summarizes the research status and development trend at home and abroad. Then, the basis of UAV track planning is introduced, including track representation, environment model establishment, such as digital terrain and common threat model, UAV kinematics performance constraint model and track evaluation. Secondly, the typical track planning algorithms are studied and compared, and the sparse A * algorithm and the genetic algorithm based track planning are introduced and verified by simulation. On this basis, an improved A * algorithm using least-square stack data structure and variable step size scheme is proposed. Aiming at the characteristic of slow convergence and premature convergence of genetic algorithm, an A search scheme for generating excellent individuals is proposed, and the simulation results are compared and analyzed. Thirdly, the 3D track avoidance method is studied, and a geometry based 3D obstacle avoidance method is proposed, and the feasibility of the algorithm is verified by simulation analysis.
【学位授予单位】：北京理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：V279

【参考文献】