Autonomous Navigation and Mapping of Water Channels in a Simulated Environment Using Micro-Aerial Vehicles

Syed Izzat Ullah, Abubakr Muhammad
{"title":"Autonomous Navigation and Mapping of Water Channels in a Simulated Environment Using Micro-Aerial Vehicles","authors":"Syed Izzat Ullah, Abubakr Muhammad","doi":"10.1109/ICRAI57502.2023.10089599","DOIUrl":null,"url":null,"abstract":"Irrigation canal networks serve as the bedrock of agriculture sectors across the globe as they are the primary channel through which water runs from major sources to agricultural lands. However, the water-carrying capacity of these water channels significantly reduces over time because of erosion, structural deterioration, and silt accumulation. As a result, routine inspections are required to analyze and repair these water channels which necessitates automation because of the vast length of the channels. We present a framework that enables Micro-Aerial Vehicles(MAVs) not only to navigate in an unknown cluttered canal environment but also to provide a complete 3-Dimensional map for the inspection. The framework consists of three main components (mapping, path planning, and mission planner) that gradually explore the environment while solving for start to local goal queries. We use Octomap; an octree-based representation of the environment for mapping, and we extended the Informed Rapidly-exploring Random Tree (Informed-RRT*) for optimal path planning and replan paths with respect to the static nearby and dynamic obstacles perceived during the execution of the mission. A simulated 2,378 meters length of canal environment is implemented and demonstrated by using the Airsim simulation in the Unreal engine, running on Robot Operation System (ROS) and Linux OS. Results obtained show that the framework enables the MAV to navigate over a simulated canal environment and allows the MAV to map the 3D structure of the canal.","PeriodicalId":447565,"journal":{"name":"2023 International Conference on Robotics and Automation in Industry (ICRAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Robotics and Automation in Industry (ICRAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRAI57502.2023.10089599","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Irrigation canal networks serve as the bedrock of agriculture sectors across the globe as they are the primary channel through which water runs from major sources to agricultural lands. However, the water-carrying capacity of these water channels significantly reduces over time because of erosion, structural deterioration, and silt accumulation. As a result, routine inspections are required to analyze and repair these water channels which necessitates automation because of the vast length of the channels. We present a framework that enables Micro-Aerial Vehicles(MAVs) not only to navigate in an unknown cluttered canal environment but also to provide a complete 3-Dimensional map for the inspection. The framework consists of three main components (mapping, path planning, and mission planner) that gradually explore the environment while solving for start to local goal queries. We use Octomap; an octree-based representation of the environment for mapping, and we extended the Informed Rapidly-exploring Random Tree (Informed-RRT*) for optimal path planning and replan paths with respect to the static nearby and dynamic obstacles perceived during the execution of the mission. A simulated 2,378 meters length of canal environment is implemented and demonstrated by using the Airsim simulation in the Unreal engine, running on Robot Operation System (ROS) and Linux OS. Results obtained show that the framework enables the MAV to navigate over a simulated canal environment and allows the MAV to map the 3D structure of the canal.
利用微型飞行器在模拟环境中自主导航和绘制水道
灌溉渠网络是全球农业部门的基石,因为它们是水从主要来源流向农业用地的主要渠道。然而,随着时间的推移,由于侵蚀、结构恶化和泥沙堆积,这些水道的携水能力显著降低。因此,需要定期检查来分析和修复这些水渠,由于水渠很长,因此需要自动化。我们提出了一个框架,使微型飞行器(MAVs)不仅可以在未知的杂乱运河环境中导航,还可以提供完整的三维地图供检查。该框架由三个主要组件(映射、路径规划和任务规划器)组成,它们在求解从起点到局部目标查询的同时逐步探索环境。我们使用Octomap;基于八叉树的环境映射表示,我们扩展了知情快速探索随机树(Informed- rrt *),用于最优路径规划,并根据执行任务过程中感知到的静态附近和动态障碍物重新规划路径。在机器人操作系统(ROS)和Linux操作系统上,利用虚幻引擎中的Airsim仿真软件,实现并演示了一个模拟2378米长的运河环境。结果表明,该框架使MAV能够在模拟的运河环境中导航,并允许MAV绘制运河的三维结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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:604180095
Book学术官方微信