UAV flight strategy algorithm based on dynamic programming

被引：6
|
作者：
Zhang Zixuan [1 ]
Wu Qinhao [2 ]
Zhang Bo [3 ]
Yi Xiaodong [1 ]
Tang Yuhua [1 ]
机构：
[1] Natl Univ Def Technol, Coll Comp, Changsha 410073, Hunan, Peoples R China
[2] Natl Univ Def Technol, Coll Elect Sci, Changsha 410073, Hunan, Peoples R China
[3] Natl Innovat Inst Def Technol, Beijing 100010, Peoples R China
来源：
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS | 2018年 / 29卷 / 06期
基金：
中国国家自然科学基金;
关键词：
motion state space; map stratification; computational complexity; dynamic programming (DP); envirommental adaptability; NETWORKS;
D O I：
10.21629/JSEE.2018.06.16
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Unmanned aerial vehicles (UAVs) may play an important role in data collection and offloading in vast areas deploying wireless sensor networks, and the UAV's action strategy has a vital influence on achieving applicability and computational complexity. Dynamic programming (DP) has a good application in the path planning of UAV, but there are problems in the applicability of special terrain environment and the complexity of the algorithm. Based on the analysis of DP, this paper proposes a hierarchical directional DP (DDP) algorithm based on direction determination and hierarchical model. We compare our methods with 0-learning and DP algorithm by experiments, and the results show that our method can improve the terrain applicability, meanwhile greatly reduce the computational complexity.
引用
收藏
页码：1293 / 1299
页数：7
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