II-New: A Heterogeneous Team of Field Robots for Research into Coordinated Monitoring of Coastal Environments

II-新：用于研究沿海环境协调监测的异构现场机器人团队

• 批准号: 1513203
• 负责人: Ioannis Rekleitis
• 金额: $ 52.1万
• 依托单位: University of South Carolina at Columbia
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-15 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1513203&HistoricalAwards=false
• 关键词: II; New; Heterogeneous; Team; Field

This infrastructure proposal supports the acquisition of a multi-robot team suited for operationsin coastal environments. The robot team consists of two underwater vehicles (AUVs), threesurface vehicles (ASVs), as well as unmanned aerial vehicles (UAVs): two fixed-wing UAVs andtwo quadrocopters. The target domain is the coastal waters of South Carolina. In several applicationssuch as environmental monitoring, homeland security, resource utilization, and contaminationtracking, there is a need to track a mass of water, record a set of properties, such as salinity,temperature, presence of different substances, and also record the position and boundariesof the said body. The proposed infrastructure will enable computing research for addressingthe above problems.This project revolves around enabling research on several CISE researchfields at the University of South Carolina, including algorithmic development for multi-robotcoordination, path-planning and state estimation; planning under uncertainty; sensor fusionfrom different modalities; and human-robot interaction.

该基础设施提案支持收购一支适合沿海环境中运营的多机器人团队。机器人团队由两辆水下车辆（AUV）组成，三杆车辆（ASV）以及无人驾驶飞机（UAVS）组成：两辆固定的无人机和四倍四倍体机器人。目标领域是南卡罗来纳州的沿海水域。在几种应用中，例如环境监测，国土安全性，资源利用和污染条件，需要跟踪大量水，记录一组属性，例如盐度，温度，存在不同的物质以及记录所述身体的位置和边界。拟议的基础设施将使计算研究能够解决上述问题。该项目围绕着在南卡罗来纳大学的几个CISE研究场上进行研究，包括用于多机构协调，路径规划和国家估计的算法开发；在不确定性下进行计划；传感器从不同的方式融合；和人类机器人的相互作用。

项目成果

Heterogeneous Multi-robot System for Exploration and Strategic Water Sampling

• DOI: 10.1109/icra.2018.8460759
• 发表时间: 2018-01-01
• 期刊: 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)
• 作者: Manjanna, Sandeep;Li, Alberto Quattrini;Dudek, Gregory
• 通讯作者: Dudek, Gregory

Experimental Comparison of Open Source Visual-Inertial-Based State Estimation Algorithms in the Underwater Domain

水下领域开源视觉惯性状态估计算法的实验比较

• 发表时间: 2019
• 期刊: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS
• 作者: Bharat Joshi, Sharmin Rahman