Vesca

韦斯卡

• 批准号: EP/R005583/1
• 负责人: Mark Else
• 金额: $ 15.21万
• 依托单位: National Institute of Agricultural Botany
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR005583%2F1
• 关键词: Vesca

Strawberry harvesting is a labour intensive task that depends critically on the availability of a large amount of low-cost labour. Growers are increasingly vulnerable to labour market price fluctuations and burdened by high employment overheads. Building on Dogtooth's proof of concept strawberry picking robot (developed during Innovate UK project Ananassa), project Vesca will deliver commercially viable picking performance using cutting edge machine learning and computer vision techniques to facilitate more efficient localization of target fruit (by more nearly optimal control of robot motion) and more accurate determination of suitability for picking. The project will also provide ancillary benefits such as yield mapping and prediction that are of significant importance to growers.

草莓采摘是一项劳动密集型任务，关键取决于大量低成本劳动力的可用性。种植者越来越容易受到劳动力市场价格波动的影响，并承受着高昂的就业间接费用。Vesca项目以Dogtooth的概念验证草莓采摘机器人（在Innovate UK项目Ananassa期间开发）为基础，将使用尖端机器学习和计算机视觉技术提供商业上可行的采摘性能，以促进更有效地定位目标水果（通过更接近最佳的控制）机器人运动）和更准确地确定采摘的适合性。该项目还将提供对种植者至关重要的产量绘图和预测等辅助效益。

项目成果

A novel 3D imaging system for strawberry phenotyping.

• DOI: 10.1186/s13007-017-0243-x
• 发表时间: 2017
• 期刊: Plant methods
• 影响因子: 5.1
• 作者: He JQ;Harrison RJ;Li B
• 通讯作者: Li B