中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Feature selection-based decision model for UAV path planning on rough terrains

文献类型:期刊论文

作者Ali, Hub5,6; Xiong, Gang4,6; Haider, Muhammad Husnain3; Tamir, Tariku Sinshaw5,6; Dong, Xisong1,6; Shen, Zhen1,2,6
刊名EXPERT SYSTEMS WITH APPLICATIONS
出版日期2023-12-01
卷号232页码:12
ISSN号0957-4174
关键词Path planning Obstacle avoidance Unmanned Aerial Vehicle (UAV) Motion planning
DOI10.1016/j.eswa.2023.120713
通讯作者Shen, Zhen(zhen.shen@ia.ac.cn)
英文摘要Path planning and obstacle avoidance in 3D terrain have been identified as a monumental challenge for a UAV in a variety of autonomous missions, such as disaster management, and search and rescue operations. In large terrain areas, it is a key problem for traditional approaches to search within the point-cloud maps to find a global path for a UAV considering the flight safety, maneuverability, weather constraints, and fuel cost. Hence, this paper proposes a trajectory planning technique for global and local path planning of a fixed-wing UAV above 3D terrain under static and dynamic constraints. For global path generation, a novel feature selection-based decision model has been proposed to select the features of a point-cloud map and transform them into the feature set. The feature set is utilized by an A* multi-directional planner with an extensive search area to deliver an optimal global path. The global path is assumed as the UAV's reference waypoints. The motion of the UAV on reference waypoints is simplified with two coordinates (R, d), where R is the cumulative distance covered by the UAV along the reference waypoints and d is its offset distance from the reference line segment in time t. For the local path planning, offset trajectories are generated along with reference waypoints to avoid collisions. Cost functions have been added so that the best global and local path can be chosen, taking into account altitude, weather, and fuel constraints. The simulation results and comparison show that the proposed approach outperforms various other 3D UAV path planning techniques in complex terrain.
WOS关键词ROBOTS ; SYSTEM
资助项目National Natural Science Foundation of China[U1909204] ; National Natural Science Foundation of China[2021B1515140034] ; Guangdong Research Foundation[RITS2021KF03] ; China Academy of Railway Sciences Corporation Limited Project[20211600200022] ; Guangdong Basic and Applied Basic Research Foundation[RITS2021KF03] ; CAS STS Dongguan Joint Project[20201600200072] ; [U19B2029]
WOS研究方向Computer Science ; Engineering ; Operations Research & Management Science
语种英语
出版者PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号WOS:001056333800001
资助机构National Natural Science Foundation of China ; Guangdong Research Foundation ; China Academy of Railway Sciences Corporation Limited Project ; Guangdong Basic and Applied Basic Research Foundation ; CAS STS Dongguan Joint Project
源URL[http://ir.ia.ac.cn/handle/173211/54101]  
专题多模态人工智能系统全国重点实验室
通讯作者Shen, Zhen
作者单位1.Qingdao Acad Intelligent Ind, Qingdao 266109, Peoples R China
2.Chinese Acad Sci, Inst Automat, 95 Zhongguancun E Rd, Beijing 100190, Peoples R China
3.Univ Elect Sci & Technol China UESTC, Sch Mech & Elect Engn, Chengdu 610054, Peoples R China
4.Chinese Acad Sci, Guangdong Engn Res Ctr 3D Printing & Intelligent M, Cloud Comp Ctr, Dongguan 523808, Peoples R China
5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
6.Chinese Acad Sci, Inst Automat, Beijing Engn Res Ctr Intelligent Syst & Technol, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Ali, Hub,Xiong, Gang,Haider, Muhammad Husnain,et al. Feature selection-based decision model for UAV path planning on rough terrains[J]. EXPERT SYSTEMS WITH APPLICATIONS,2023,232:12.
APA Ali, Hub,Xiong, Gang,Haider, Muhammad Husnain,Tamir, Tariku Sinshaw,Dong, Xisong,&Shen, Zhen.(2023).Feature selection-based decision model for UAV path planning on rough terrains.EXPERT SYSTEMS WITH APPLICATIONS,232,12.
MLA Ali, Hub,et al."Feature selection-based decision model for UAV path planning on rough terrains".EXPERT SYSTEMS WITH APPLICATIONS 232(2023):12.

入库方式: OAI收割

来源:自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。