Vesca

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。基于Dogtooth的草莓采摘机器人概念验证（在Innovate UK项目Ananassa期间开发），Vesca项目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（通过更接近最佳的机器人运动控制）和更准确地确定采摘的适用性。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。

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.