无人飞行器航迹规划算法的综述
首发时间:2017-04-05
摘要:总结了分层航迹规划的一般步骤:环境及威胁建模, 全局航迹规划,航迹在线修正和路径平滑。针对无人飞行器任务环境复杂,突发威胁严重,动力约束严格,实时性要求高等特点,综述了常用的几种航迹规划算法的特点,根据各算法的特点,归纳出各航迹规划算法的适用范围。如人工势场法适合实时性和安全性较高的航迹规划;传统A*算法和遗传算法适合解决离线全局的航迹规划问题,不适合用于实时规划;粒子群优化算法和蚁群算法适合复杂环境下的快速求解问题,适合动态,并行协作航迹规划;混合算法可以选择不同的算法用于不同环境的航迹规划。分析了特殊环境下航迹规划算法的选择策略,如军事环境和灾害救援环境,这两种环境都相对复杂,不确定性较大,是动态变化的,所以这两种特殊环境下常用的航迹规划算法有人工势场算法和融合合算法等提高航迹规划的适用性。最后分别从航迹规划的可靠性,安全性,适用性展望了无人飞行器航迹规划。
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Overview of UAV flight path planning algorithm
Abstract:The general steps of UAV flight path planning are summarized,which include environment and threat modeling, global path planning, Online path correction,path smoothing.Aiming at the characteristics of the unmanned aerial vehicle (UAV), such as the complex task environment, the serious threat, the strict dynamic constraints, and the high real-time requirements, this paper summarizes the characteristics of several common path planning algorithms,According to the characteristics of each algorithm, the application range of each route planning algorithm is summarized.Such as the artificial potential field method is suitable for the real time and high safety track planning;The traditional A* algorithm is suitable for solving the problem of global static path planning;The genetic algorithm is suitable for global off-line planning,and is not suitable for real-time planning;Particle swarm optimization (PSO) algorithm is suitable for fast solving problems in complex environment;Ant colony algorithm is suitable for dynamic and parallel cooperative path planning; The hybrid algorithm can choose different algorithms for different environments.The strategy of path planning algorithm is analyzed under special circumstances,such as the military environment and disaster relief environment,these two environments are relatively complex, the uncertainty is large, strong variability,therefore, these two kinds of special environment are commonly used dynamic programming algorithm, artificial potential field algorithm, genetic algorithm, sparse A* algorithm, and hybrid algorithm.In the end, the flight path planning of unmanned aerial vehicle (UAV) is discussed from the aspects of reliability, safety and applicability.
Keywords: UAV flight path planning algorithm Path planning algorithm
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