Collaborative Research: NRI: INT: Cooperative Underwater Structure Inspection and Mapping
合作研究:NRI:INT:合作水下结构检查和测绘
基本信息
- 批准号:2024541
- 负责人:
- 金额:$ 40.34万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-10-01 至 2024-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This project develops a system of co-robots collaborating with a human operator to map underwater structures. Underwater structure mapping is an important capability applicable to multiple domains: marine archaeology, infrastructure maintenance, resource utilization, security, and environmental monitoring. The underwater environment is challenging and dangerous for humans in many aspects, while robotic operations face additional challenges compared to the above-water ones. In particular, both sensing and communications are restricted, and planning is required in three dimensions with limited information. The project will generate a 3D model of the underwater structure providing a high-resolution photo-realistic representation. Autonomous Underwater Vehicles (AUVs)will be operating in close cooperation, generating a dense vision-based reconstruction of the observed surface, and coordinated with remote human operators.. The project integrates research and education through training of undergraduate and graduate students, who will have the opportunity to work in an inclusive, interdisciplinary team across South Carolina, New Jersey, and New Hampshire. The system will be integrated and tested for archaeological mapping at field sites. Research will be conducted along three directions. (1) Robust underwater state estimation based on a deep learning approach and a hybrid representation for 3-D reconstruction that will encode probabilistic occupancy for both navigation and initial inspection from users. (2) Collaborative planning, for the proximal observers based on a local optimization framework that originally considers multiple criteria, including information gain, uncertainty reduction, and loop closure, active positioning of distal observers, and user preference to make joint measurements and inform proximal observers on where to go. (3) Information driven communications, with careful design of efficient data representation of the 3-D reconstruction and of a cross-layer optimization for deciding when and how to share. These three components will contribute towards the overarching goal of enabling a team of co-robots to operate autonomously and produce a realistic map of an underwater structure.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
该项目开发了与人类操作员合作以绘制水下结构的共同机器人系统。水下结构映射是适用于多个领域的重要功能:海洋考古学,基础设施维护,资源利用,安全性和环境监控。在许多方面,水下环境对人类具有挑战性和危险,而与上述水相比,机器人操作面临着其他挑战。特别是,感应和通信受到限制,并且在三个维度中需要计划有限的信息。该项目将生成水下结构的3D模型,从而提供高分辨率的照片现实代表。自动驾驶水下车辆(AUV)将在密切合作中运作,产生基于观察到的表面的密集重建,并与遥远的人类运营商进行协调。该项目通过对本科生和研究生的培训来整合研究和教育,他们将有机会在南卡罗来纳州南卡罗来纳州,新Jersey,New Jersey和New Hampshire和New Jersey和New Hampshire的整个跨学科团队中工作。该系统将在现场位点进行集成和测试,以进行考古映射。 研究将沿三个方向进行。 (1)基于深度学习方法的强大水下状态估计以及3-D重建的混合表示,将对用户的导航和初步检查编码概率占用。 (2)基于本地优化框架的近端观察者的合作计划,该框架最初考虑了多个标准,包括信息增益,降低不确定性和循环封闭,远端观察者的主动定位以及用户的优先选择,以进行关节测量并告知近端观察者。 (3)信息驱动的通信,并仔细设计了3-D重建的有效数据表示以及用于决定何时以及如何共享的跨层优化。这三个组成部分将有助于使一组共同机器人团队自主操作并制作出水下结构的现实地图。该奖项反映了NSF的法定任务,并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来通过评估来获得支持的。
项目成果
期刊论文数量(11)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
SVIn2: A multi-sensor fusion-based underwater SLAM system
- DOI:10.1177/02783649221110259
- 发表时间:2022-07-13
- 期刊:
- 影响因子:9.2
- 作者:Rahman, Sharmin;Quattrini Li, Alberto;Rekleitis, Ioannis
- 通讯作者:Rekleitis, Ioannis
Deep Underwater Monocular Depth Estimation with Single-Beam Echosounder
使用单波束回声测深仪进行深水下单目深度估计
- DOI:10.1109/icra48891.2023.10161439
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Liu, Haowen;Roznere, Monika;Quattrini Li, Alberto
- 通讯作者:Quattrini Li, Alberto
Communication for Underwater Robots: Recent Trends
- DOI:10.1007/s43154-023-00100-4
- 发表时间:2023-06
- 期刊:
- 影响因子:0
- 作者:Alberto Quattrini Li;Charles J. Carver;Qijia Shao;Xia Zhou;Srihari Nelakuditi
- 通讯作者:Alberto Quattrini Li;Charles J. Carver;Qijia Shao;Xia Zhou;Srihari Nelakuditi
DeepURL: Deep Pose Estimation Framework for Underwater Relative Localization
- DOI:10.1109/iros45743.2020.9341201
- 发表时间:2020-03
- 期刊:
- 影响因子:0
- 作者:Bharat Joshi;M. Modasshir;Travis Manderson;Hunter Damron;M. Xanthidis;Alberto Quattrini Li;Ioannis M. Rekleitis;G. Dudek
- 通讯作者:Bharat Joshi;M. Modasshir;Travis Manderson;Hunter Damron;M. Xanthidis;Alberto Quattrini Li;Ioannis M. Rekleitis;G. Dudek
Real-Time Dense 3D Mapping of Underwater Environments
水下环境的实时密集 3D 测绘
- DOI:10.1109/icra48891.2023.10160266
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Wang, Weihan;Joshi, Bharat;Burgdorfer, Nathaniel;Batsos, Konstantinos;Quattrini Li, Alberto;Mordohai, Philippos;Rekleitis, Ioannis
- 通讯作者:Rekleitis, Ioannis
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Alberto Quattrini Li其他文献
Towards the autonomous underwater construction of cement block structures with free-floating robots
利用自由漂浮机器人进行水泥块结构水下自主施工
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Samuel Lensgraf;A. Sniffen;Alberto Quattrini Li;Devin J. Balkcom - 通讯作者:
Devin J. Balkcom
Sunflower: locating underwater robots from the air: video
向日葵:从空中定位水下机器人:视频
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Charles J. Carver;Qijia Shao;Samuel Lensgraf;A. Sniffen;Maxine Perroni;Hunter Gallant;Alberto Quattrini Li;Xia Zhou - 通讯作者:
Xia Zhou
Vision-based shipwreck mapping: On evaluating features quality and open source state estimation packages
基于视觉的沉船测绘:评估特征质量和开源状态估计包
- DOI:
- 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
Alberto Quattrini Li;A. Coskun;S. M. Doherty;S. Ghasemlou;A. S. Jagtap;M. Modasshir;S. Rahman;A. Singh;M. Xanthidis;J. O’Kane;Ioannis M. Rekleitis - 通讯作者:
Ioannis M. Rekleitis
External Force Field Modeling for Autonomous Surface Vehicles
自主地面车辆的外力场建模
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
Jason Moulton;N. Karapetyan;Alberto Quattrini Li;Ioannis M. Rekleitis - 通讯作者:
Ioannis M. Rekleitis
Experimental Analysis of Radio Communication Capabilities of Multiple Autonomous Surface Vehicles
多自主水面车辆无线电通信能力实验分析
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
S. Malebary;Jason Moulton;Alberto Quattrini Li;Ioannis M. Rekleitis - 通讯作者:
Ioannis M. Rekleitis
Alberto Quattrini Li的其他文献
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{{ truncateString('Alberto Quattrini Li', 18)}}的其他基金
CAREER: Resilient Low-Cost Robot Teams for Autonomous Aquatic Exploration
职业:用于自主水生探索的有弹性的低成本机器人团队
- 批准号:
2144624 - 财政年份:2022
- 资助金额:
$ 40.34万 - 项目类别:
Continuing Grant
MRI: Track-1: Acquisition of marine multirobot systems for underwater monitoring and construction
MRI:Track-1:采购用于水下监测和施工的海洋多机器人系统
- 批准号:
1919647 - 财政年份:2019
- 资助金额:
$ 40.34万 - 项目类别:
Standard Grant
RII Track-2 FEC: Computational Methods and Autonomous Robotics Systems for Modeling and Predicting Harmful Cyanobacterial Blooms
RII Track-2 FEC:用于建模和预测有害蓝藻水华的计算方法和自主机器人系统
- 批准号:
1923004 - 财政年份:2019
- 资助金额:
$ 40.34万 - 项目类别:
Cooperative Agreement
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