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

目前的作物生产系统一直依赖于大规模使用除草剂来控制杂草。然而，由于前所未有的监管和环境压力，这种方法是不可持续的，这些压力使得开发新的杀草技术成为新的重点。该项目将研究下一代机器人除草机械的技术基础，实现对特定杂草的选择性和精确处理。所提出的技术是低成本的3D传感和学习软件与合适的杂草清除技术的新颖结合。拟议的发展将带来更高效的文化除草设备，从而更好地管理杂草，减少投入使用，为食品生产商、销售商和社会带来一些好处。

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.