运动规划
初始化
网格
路径(计算)
计算机科学
数学优化
粒子群优化
网格法乘法
比例(比率)
群体行为
维数(图论)
人工智能
数学
地理
机器人
地图学
程序设计语言
纯数学
几何学
出处
期刊:International journal of applied earth observation and geoinformation
日期:2022-12-01
卷期号:115: 103133-103133
被引量:14
标识
DOI:10.1016/j.jag.2022.103133
摘要
Path planning is an important problem in the field of unmanned aerial vehicles (UAVs), particularly in complex environments; however, existing path planning methods have certain limitations and yield poor results. For a better solution to the path planning problem, we propose an adaptive path planning method for UAVs in complex environments. This method is based on discrete global grid systems for conflict detection between the airspace and UAV path. A multi-scale discrete layered grid model that provides a new management framework for the discrete global grid and accelerates conflict detection is proposed for complex environments. Thereafter, the particle swarm optimization (PSO) was exploited to develop an adaptive path planning PSO (APP-PSO) method, which was improved in terms of dimension, initialization, and iteration update strategy to plan an optimal path. Finally, the proposed method was validated by comparison with other related PSO algorithms and several simulation-based experiments illustrating its optimality.
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