Autonomous Drones for Nature Conservation Missions
用于自然保护任务的自主无人机
基本信息
- 批准号:EP/X029077/1
- 负责人:
- 金额:$ 67.6万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2023
- 资助国家:英国
- 起止时间:2023 至 无数据
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
The aim of WildDrone is to push wildlife conservation practices into the 21st century. The need for effective, cost-efficient conservation practices are greater than ever as we currently face the greatest loss of global biodiversity in history. Present conservation practices are typically very labour intensive, costly, and time-consuming. Collected data is often inaccurate or incomplete. However, recent advances in drone technology have shown that this technology has great potential as a practical tool for conservationists and that it could potentially revolutionize our efforts in nature conservation. Nevertheless, drone technology is still a developing field and many obstacles stand in the way of us harvesting the benefits of this emerging technology. To fully achieve its promising potential in this new domain we will need to invent more robust and predictable robotic technologies, including effective and automated means of gathering and interpreting ecological and behavioural data. WildDrone will address these challenges by joining the scientific areas of aerial robotics, computer vision, and wildlife ecology. The network proposes to develop new autonomous drone technology, expand current computer vision capabilities, and combine these advances to create practical tools for visual inspection and monitoring of wildlife populations. This drone-based inspection will provide conservationists with crucial knowledge of animal health, behaviour, and numbers. These challenges will be solved by 11 PhDs (one self-funded). An interdisciplinary research training programme has been designed to educate a new generation of PhDs and provide them with a unique skill set enabling them to tackle the great challenges we must solve collectively, if we are to reverse the decline of global biodiversity. This program will raise the level of excellence in doctoral programs and simultaneously enhance the career perspectives of the PhDs in both academia and industry.
WildDrone的目标是将野生动物保护实践推向21世纪。由于我们目前面临着历史上最大的全球生物多样性损失,对有效、成本效益高的保护做法的需求比以往任何时候都更加迫切。目前的保护做法通常是非常劳动密集型的、昂贵的和耗时的。收集的数据往往不准确或不完整。然而,无人机技术的最新进展表明,这项技术作为环保主义者的实用工具具有巨大的潜力,它可能会彻底改变我们在自然保护方面的努力。然而,无人机技术仍然是一个发展中的领域,许多障碍阻碍了我们从这项新兴技术中获益。为了充分发挥其在这一新领域的潜力,我们将需要发明更强大和可预测的机器人技术,包括收集和解释生态和行为数据的有效和自动化手段。WildDrone将通过加入空中机器人、计算机视觉和野生动物生态等科学领域来应对这些挑战。该网络建议开发新的自主无人机技术,扩展当前的计算机视觉能力,并将这些进步结合起来,为野生动物种群的视觉检查和监测创造实用工具。这种基于无人机的检查将为动物保护者提供关于动物健康、行为和数量的关键知识。这些挑战将由11名博士(一名自费)来解决。已经设计了一个跨学科的研究培训方案,以教育新一代博士,并为他们提供独特的技能,使他们能够应对我们必须共同解决的重大挑战,如果我们要扭转全球生物多样性的衰退。该项目将提高博士项目的卓越水平,同时增强学术界和产业界博士的职业前景。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Thomas Richardson其他文献
Left-handed fighters are overrepresented and more successful in combat sports
左撇子拳击手在格斗运动中所占比例较高且更为成功
- DOI:
10.17605/osf.io/x3unr - 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Thomas Richardson - 通讯作者:
Thomas Richardson
Young, formidable men show greater sensitivity to facial cues of dominance
年轻而强大的男性对面部主导地位的暗示更加敏感
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:5.1
- 作者:
Thomas Richardson;M. Waddington;R. Tucker Gilman - 通讯作者:
R. Tucker Gilman
Generalizing minimum safe operating altitudes for fixed‐wing UAVs in real‐time
实时概括固定翼无人机的最低安全操作高度
- DOI:
10.1002/rob.22331 - 发表时间:
2024 - 期刊:
- 影响因子:8.3
- 作者:
Ashford Milne;Alex McConville;Thomas Richardson;Matt Watson;Ben Schellenberg - 通讯作者:
Ben Schellenberg
Does Childhood Trauma Predict Impulsive Spending in Later Life? An Analysis of the Mediating Roles of Impulsivity and Emotion Regulation
童年创伤是否预示着晚年的冲动消费?
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Thomas Richardson;Annelise Egglishaw;Monica Sood - 通讯作者:
Monica Sood
The effect of SiC additives on the cycling performance of CaCOsub3/sub when used as a high-temperature thermal battery
碳化硅添加剂对碳酸钙作为高温热电池时循环性能的影响
- DOI:
10.1016/j.jallcom.2022.167844 - 发表时间:
2023-02-10 - 期刊:
- 影响因子:6.300
- 作者:
Thomas Richardson;Rajani K. Vijayaraghavan;Patrick J. McNally;M. Veronica Sofianos - 通讯作者:
M. Veronica Sofianos
Thomas Richardson的其他文献
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{{ truncateString('Thomas Richardson', 18)}}的其他基金
Dissecting the molecular aetiology of complex traits using high dimensional omic data
使用高维组学数据剖析复杂性状的分子病因学
- 批准号:
MR/S003886/1 - 财政年份:2018
- 资助金额:
$ 67.6万 - 项目类别:
Fellowship
Collaborative Research: Graphical and Algebraic Models for Multivariate Categorical Data
协作研究:多元分类数据的图形和代数模型
- 批准号:
0505865 - 财政年份:2005
- 资助金额:
$ 67.6万 - 项目类别:
Standard Grant
Graphical Markov Models with Interpretable Structure
具有可解释结构的图形马尔可夫模型
- 批准号:
9972008 - 财政年份:1999
- 资助金额:
$ 67.6万 - 项目类别:
Continuing Grant
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