Fast Generation of Chance-Constrained Flight Trajectory for Unmanned Vehicles

doi:10.1109/TAES.2020.3037417

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 智能机器人系统研究

	Fast Generation of Chance-Constrained Flight Trajectory for Unmanned Vehicles
	Chai, Runqi 1; Tsourdos, Antonios 1; Al Savvaris 1; Wang, Shuo2 ; Xia, Yuanqing 3; Chai, Senchun 3
发表期刊	IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
ISSN	0018-9251
	2021-04-01
卷号	57 期号:2 页码:1028-1045
通讯作者	Chai, Runqi(r.chai@cranfield.ac.uk)
摘要	In this article, a fast chance-constrained trajectory generation strategy incorporating convex optimization and convex approximation of chance constraints is designed so as to solve the unmanned vehicle path planning problem. A path-length-optimal unmanned vehicle trajectory optimization model is constructed with the consideration of the pitch angle constraint, the curvature radius constraint, the probabilistic control actuation constraint, and the probabilistic collision avoidance constraint. Subsequently, convexification technique is introduced to convert the nonlinear problem formulation into a convex form. To deal with the probabilistic constraints in the optimization model, convex approximation techniques are introduced such that the probabilistic constraints are replaced by deterministic ones while simultaneously preserving the convexity of the optimization model. Numerical results, obtained from a number of case studies, validate the effectiveness and reliability of the proposed approach. A number of comparative studies were also performed. The results confirm that the proposed design is able to produce more optimal flight paths and achieve enhanced computational performance than other chance-constrained optimization approaches investigated in this article.
关键词	Unmanned aerial vehicles Probabilistic logic Trajectory optimization Mathematical model Aerodynamics Vehicle dynamics Trajectory planning Chance constrained convex approximation convex optimization convexification trajectory optimization unmanned vehicle
DOI	10.1109/TAES.2020.3037417
关键词[WOS]	POWERED DESCENT ; PATH GENERATION ; OPTIMIZATION ; TRACKING
收录类别	SCI
语种	英语
WOS研究方向	Engineering ; Telecommunications
WOS类目	Engineering, Aerospace ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000639747300019
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：20[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/44510
专题	多模态人工智能系统全国重点实验室_智能机器人系统研究
通讯作者	Chai, Runqi
作者单位	1.Cranfield Univ, Sch Aerosp Transport & Mfg, Cranfield MK43 0AL, Beds, England 2.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China 3.Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China
推荐引用方式 GB/T 7714	Chai, Runqi,Tsourdos, Antonios,Al Savvaris,et al. Fast Generation of Chance-Constrained Flight Trajectory for Unmanned Vehicles[J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS,2021,57(2):1028-1045.
APA	Chai, Runqi,Tsourdos, Antonios,Al Savvaris,Wang, Shuo,Xia, Yuanqing,&Chai, Senchun.(2021).Fast Generation of Chance-Constrained Flight Trajectory for Unmanned Vehicles.IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS,57(2),1028-1045.
MLA	Chai, Runqi,et al."Fast Generation of Chance-Constrained Flight Trajectory for Unmanned Vehicles".IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 57.2(2021):1028-1045.