中国科学院深圳先进技术研究院机构知识库(SIAT OpenIR): Geometric Reinforcement Learning for Path Planning of UAVs
SIAT OpenIR  > 集成所
Geometric Reinforcement Learning for Path Planning of UAVs
Zhang Baochang; Mao Zhili; Liu Wanquan; Liu Jianzhuang
2015
Source PublicationJOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
Subtype期刊论文
AbstractWe proposed a new learning algorithm, named Geometric Reinforcement Learning (GRL), for path planning of Unmanned Aerial Vehicles (UAVs). The contributions of GRL are as: (1) GRL exploits a specific reward matrix, which is simple and efficient for path planning of multiple UAVs. The candidate points are selected from the region along the Geometric path from the current point to the target point. (2) The convergence of calculating the reward matrix is theoretically proven, and the path in terms of path length and risk measure can be calculated. (3) In GRL, the reward matrix is adaptively updated based on the Geometric distance and risk information shared by other UAVs. Extensive experimental results validate the effectiveness and feasibility of GRL on the navigation of UAVs
URL查看原文
Indexed BySCI
Language英语
Department多媒体集成技术研究中心
Document Type期刊论文
Identifierhttp://ir.siat.ac.cn/handle/172644/6565
Collection集成所
AffiliationJOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
Recommended Citation
GB/T 7714
Zhang Baochang,Mao Zhili,Liu Wanquan,et al. Geometric Reinforcement Learning for Path Planning of UAVs[J]. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS,2015.
APA Zhang Baochang,Mao Zhili,Liu Wanquan,&Liu Jianzhuang.(2015).Geometric Reinforcement Learning for Path Planning of UAVs.JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS.
MLA Zhang Baochang,et al."Geometric Reinforcement Learning for Path Planning of UAVs".JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS (2015).
Files in This Item: Download All
File Name/Size DocType Version Access License
集成-多媒体2015017.pdf(2392KB) 开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhang Baochang]'s Articles
[Mao Zhili]'s Articles
[Liu Wanquan]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhang Baochang]'s Articles
[Mao Zhili]'s Articles
[Liu Wanquan]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhang Baochang]'s Articles
[Mao Zhili]'s Articles
[Liu Wanquan]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 集成-多媒体2015017.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.