粗糙地形下无人机自主安全着陆点选择研究

Wenlong Zheng, Jianjun Yi, Hao Xiang, Bo Zhou, Danwei W. Wang, Changchun Zhao
{"title":"粗糙地形下无人机自主安全着陆点选择研究","authors":"Wenlong Zheng, Jianjun Yi, Hao Xiang, Bo Zhou, Danwei W. Wang, Changchun Zhao","doi":"10.1145/3448734.3450884","DOIUrl":null,"url":null,"abstract":"Autonomous safe landing of UAV is an important function in many scenarios such as force landing and delivery. This paper proposes a method to autonomously select a safe landing site for vertical take-off and landing (VTOL) UAV based on point cloud, which can minimize combined risks posed during touch down at the chosen landing site. The most suitable landing site of a landing zone is selected according to the terrain complexity. In this paper, (1) fine-grained grid elevation map converted from the terrain point cloud is used to calculate the potential risk such as slope, roughness and maximum height difference. (2) A comprehensive risk model is designed to consider all above risks to recognize obstacles and risk areas, and combine the flight distance factors to obtain the final cost map. (3) We process cost map as image by OpenCV to accelerate the processing and reduce reaction time. Terrain point clouds of simulation scene and real world are used for experiments and experimental results show that the selected landing sites can meet the safety requirements, which demonstrate the effectiveness and feasibility of our proposed method.","PeriodicalId":105999,"journal":{"name":"The 2nd International Conference on Computing and Data Science","volume":"326 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Study for UAV Autonomous Safe Landing-Site Selection on Rough Terrain\",\"authors\":\"Wenlong Zheng, Jianjun Yi, Hao Xiang, Bo Zhou, Danwei W. Wang, Changchun Zhao\",\"doi\":\"10.1145/3448734.3450884\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Autonomous safe landing of UAV is an important function in many scenarios such as force landing and delivery. This paper proposes a method to autonomously select a safe landing site for vertical take-off and landing (VTOL) UAV based on point cloud, which can minimize combined risks posed during touch down at the chosen landing site. The most suitable landing site of a landing zone is selected according to the terrain complexity. In this paper, (1) fine-grained grid elevation map converted from the terrain point cloud is used to calculate the potential risk such as slope, roughness and maximum height difference. (2) A comprehensive risk model is designed to consider all above risks to recognize obstacles and risk areas, and combine the flight distance factors to obtain the final cost map. (3) We process cost map as image by OpenCV to accelerate the processing and reduce reaction time. Terrain point clouds of simulation scene and real world are used for experiments and experimental results show that the selected landing sites can meet the safety requirements, which demonstrate the effectiveness and feasibility of our proposed method.\",\"PeriodicalId\":105999,\"journal\":{\"name\":\"The 2nd International Conference on Computing and Data Science\",\"volume\":\"326 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 2nd International Conference on Computing and Data Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3448734.3450884\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2nd International Conference on Computing and Data Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3448734.3450884","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

无人机的自主安全著陆是在强制著陆和投送等多种场景下的重要功能。本文提出了一种基于点云的垂直起降无人机安全着陆点自主选择方法,可最大限度地降低所选着陆点着陆过程中的综合风险。根据地形复杂程度选择着陆区的最合适着陆点。本文(1)利用地形点云转换成的细粒度网格高程图,计算坡度、粗糙度、最大高差等潜在风险;(2)设计综合风险模型,综合考虑上述风险,识别障碍和风险区域,并结合飞行距离因素,得到最终的成本图。(3)采用OpenCV将成本图处理为图像,加快了处理速度,缩短了反应时间。利用仿真场景和真实世界的地形点云进行了实验,实验结果表明所选择的着陆点能够满足安全要求,验证了所提方法的有效性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study for UAV Autonomous Safe Landing-Site Selection on Rough Terrain
Autonomous safe landing of UAV is an important function in many scenarios such as force landing and delivery. This paper proposes a method to autonomously select a safe landing site for vertical take-off and landing (VTOL) UAV based on point cloud, which can minimize combined risks posed during touch down at the chosen landing site. The most suitable landing site of a landing zone is selected according to the terrain complexity. In this paper, (1) fine-grained grid elevation map converted from the terrain point cloud is used to calculate the potential risk such as slope, roughness and maximum height difference. (2) A comprehensive risk model is designed to consider all above risks to recognize obstacles and risk areas, and combine the flight distance factors to obtain the final cost map. (3) We process cost map as image by OpenCV to accelerate the processing and reduce reaction time. Terrain point clouds of simulation scene and real world are used for experiments and experimental results show that the selected landing sites can meet the safety requirements, which demonstrate the effectiveness and feasibility of our proposed method.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信