HUman-machine teaming for Maritime Environments (HUME)
HUman-machine teaming for Maritime Environments (HUME)
批准号:
EP/V05676X/1
负责人:
Helen Hastie
金额:
$143.97万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --
中文摘要
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英文摘要
The offshore energy and defence sectors share a vision of the future where people are taken out of harsh, extreme environments and replaced by teams of smart robots able to do the 'dirty and dangerous jobs', collaborating seamlessly as a team with each other and with the human operators and experts on-shore. In this new world, remote data collection, fusion and interpretation become central, together with the ability to generate transparent, safe actionable decisions from this data. We propose the HUME project (HUman-machine teaming for Maritime Environments), whose vision is to develop a coherent framework that enables humans and machines to work seamlessly as a team by establishing and maintaining a single shared view of the world and each other's intents through transparent interaction, robust to a highly dynamic and unpredictable maritime environments. The HUME project's ambitious and fundamental research programme will address fundamental research questions in the field of machine-machine and human-machine collaboration, robot perception and explainable autonomy and AI. The Prosperity Partnership would build on a 20 year strategic relationship between SeeByte and HWU, with SeeByte originally a spin-out of Heriot-Watt University in 2001 and now a world-leader in maritime autonomy worldwide in the Oil & Gas and Defence sectors. This grant would facilitate a shift to lower TRL research and development, providing seeding for early-stage research that can have a broad, longer-term and more disruptive impact. This proposed work aims at establishing a durable model, through which SeeByte and HWU can remain connected to foster long-term research relationships on projects of interest, as they emerge in this rapidly changing field.
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Self-Explainable Robots in Remote Environments
远程环境中的自解释机器人
DOI:
--
发表时间:
2021
期刊:
影响因子:
--
作者:
[Chiyah Garcia, F. J.]
通讯作者:
Chiyah Garcia, F. J.
Explanation Styles for Trustworthy Autonomous Systems
值得信赖的自治系统的解释风格
DOI:
--
发表时间:
2023
期刊:
影响因子:
--
作者:
[David A. Robb]
通讯作者:
David A. Robb
From market-ready ROVs to low-cost AUVs
从市场就绪的 ROV 到低成本 AUV
DOI:
10.23919/oceans44145.2021.9705798
发表时间:
2021
期刊:
影响因子:
--
作者:
[Willners J]
通讯作者:
Willners J
DOI:
--
发表时间:
2022
期刊:
影响因子:
--
作者:
[Konstantinos Gavriilidis]
通讯作者:
Konstantinos Gavriilidis
Learning to Read Maps: Understanding Natural Language Instructions from Unseen Maps
学习阅读地图:从看不见的地图中理解自然语言指令
DOI:
--
发表时间:
2021
期刊:
影响因子:
--
作者:
[Katsakioris MM]
通讯作者:
Katsakioris MM
共 8 条
UKRI Trustworthy Autonomous Systems Node in Trust
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批准号:EP/V026682/1
-
项目类别:Research Grant
-
资助金额:$389.49万
-
财政年份:2020
-
负责人:Helen Hastie
-
依托单位:
国内基金
海外基金
Understanding structural evolution of galaxies with machine learning
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批准号:
-
项目类别:省市级项目
-
资助金额:10.0万元
-
批准年份:2022
-
负责人:Nicola Rosario Napolitano
-
依托单位:
非标准随机调度模型的最优动态策略
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批准号:71071056
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项目类别:面上项目
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资助金额:28.0万元
-
批准年份:2010
-
负责人:吴贤毅
-
依托单位:
微生物发酵过程的自组织建模与优化控制
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批准号:60704036
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项目类别:青年科学基金项目
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资助金额:21.0万元
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批准年份:2007
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负责人:高学金
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依托单位: