3D Vision-based Crop-Weed Discrimination for Automated Weeding Operations

目前的作物生产体系一直依赖于除草剂的广泛应用来控制杂草。然而，这种方法是不可持续的，因为前所未有的监管和环境压力将新的重点放在了开发新的除草技术上。这个项目将研究下一代机器人除草机械的技术基础，使其能够选择性和准确地处理特定的杂草。所提出的技术是低成本3D传感和学习软件与合适的除草技术的完美结合。拟议的发展将导致更高效的栽培除草设备，从而更好地管理杂草和减少投入使用，为粮食生产者、销售商和社会带来几个好处。

The current crop production systems have been reliant on the wide-scale application of herbicides tocontrol weeds. However, this approach is not sustainable due to unprecedented regulatory andenvironmental pressures which place new emphasis on the development of novel techniques to killweeds.This project will investigate the technical foundations for the next generation of robotic weedingmachinery, enabling selective and accurate treatment of specific weeds. The proposed technology is anovel combination of low-cost 3D sensing and learning software together with a suitable weeddestruction technique. The proposed developments will lead to more efficient cultural weedingequipment resulting in better management of weeds and reduced input use, bringing several benefits tofood producers, sellers and society.