Multi-UAV Information Fusion and Cooperative Trajectory Optimization in Target Search

被引:16
作者
Yao, Peng [1 ,2 ]
Wei, Xin [1 ,2 ]
机构
[1] Ocean Univ China, Shandong Prov Key Lab Ocean Engn, Qingdao 266100, Peoples R China
[2] Ocean Univ China, Coll Engn, Qingdao 266100, Peoples R China
来源
IEEE SYSTEMS JOURNAL | 2022年 / 16卷 / 03期
基金
中国国家自然科学基金;
关键词
Communication networks; Trajectory optimization; Task analysis; Consensus algorithm; Mathematical models; Interference; Convergence; Communication performance; information fusion; multiunmanned aerial vehicles (UAVs); search perfor-mance; trajectory optimization; GAUSSIAN MIXTURE MODEL; NETWORKS;
D O I
10.1109/JSYST.2021.3117959
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the increasing complexity of the search environment, it is particularly important for multiunmanned aerial vehicles (UAVs) to achieve a safe and efficient search for a dynamic target. For the communication network and information fusion among multi-UAVs, we adopt the minimum spanning tree structure as the communication network, and then based on this structure, the consensus algorithm with state predictor is utilized for the fusion of predicted target probability map. Moreover, based on the traditional model predictive control (MPC), the future-dependent MPC framework is proposed to realize the cooperative trajectory optimization and obtain the optimal control input, and especially the objective function of trajectory optimization is established by considering comprehensively the communication performance and the search performance. Finally, the feasibility of our method in the multi-UAV cooperative search task is verified via simulation.
引用
收藏
页码:4325 / 4333
页数:9
相关论文
共 28 条
[1]   An innovative multi-agent search-and-rescue path planning approach [J].
Berger, Jean ;
Lo, Nassirou .
COMPUTERS & OPERATIONS RESEARCH, 2015, 53 :24-31
[2]  
Bourgault F, 2006, SPRINGER TRAC ADV RO, V24, P209
[3]   Analysis of Search Decision Making Using Probabilistic Search Strategies [J].
Chung, Timothy H. ;
Burdick, Joel W. .
IEEE TRANSACTIONS ON ROBOTICS, 2012, 28 (01) :132-144
[4]   Potential field based receding horizon motion planning for centrality-aware multiple UAV cooperative surveillance [J].
Di, Bin ;
Zhou, Rui ;
Duan, Haibin .
AEROSPACE SCIENCE AND TECHNOLOGY, 2015, 46 :386-397
[5]   A survey on coverage path planning for robotics [J].
Galceran, Enric ;
Carreras, Marc .
ROBOTICS AND AUTONOMOUS SYSTEMS, 2013, 61 (12) :1258-1276
[6]   Search Strategies for Multiple UAV Search and Destroy Missions [J].
George, Joel ;
Sujit, P. B. ;
Sousa, J. B. .
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2011, 61 (1-4) :355-367
[7]   Side-to-side 3D coverage path planning approach for agricultural robots to minimize skip/overlap areas between swaths [J].
Hameed, I. A. ;
la Cour-Harbo, A. ;
Osen, O. L. .
ROBOTICS AND AUTONOMOUS SYSTEMS, 2016, 76 :36-45
[8]   Multiagent Information Fusion and Cooperative Control in Target Search [J].
Hu, Jinwen ;
Xie, Lihua ;
Lum, Kai-Yew ;
Xu, Jun .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2013, 21 (04) :1223-1235
[9]   Time-Efficient and Complete Coverage Path Planning Based on Flow Networks for Multi-Robots [J].
Janchiv, Adiyabaatar ;
Batsaikhan, Dugarjav ;
Kim, ByungSoo ;
Lee, Won Gu ;
Lee, Soon-Geul .
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2013, 11 (02) :369-376
[10]   Information Exchange and Decision Making in Micro Aerial Vehicle Networks for Cooperative Search [J].
Khan, Asif ;
Yanmaz, Evsen ;
Rinner, Bernhard .
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS, 2015, 2 (04) :335-347