Key Technologies and Prospects of Laser Weeding Robots

doi:10.12133/j.smartag.SA202410031

Abstract

Abstract:

[Significance] Grass damage in farmland seriously restricts the quality and yield of crop planting and production, and promotes the occurrence of pests and diseases. Weed control is a necessary measure for high yield and high quality of crops. Currently, there are five main weed control methods: Manual, biological, thermal, mechanical, and chemical weed control. Traditional chemical weed control methods are gradually limited due to soil pollution and ecological balance disruption. Intelligent laser weeding technology, with the characteristics of environmental protection, high efficiency, flexibility, and automation, as an emerging and promising ecological and environmental protection new object control method for field weeds, has become the core direction to replace chemical weeding in recent years. The laser weeding robot is the carrier of laser weeding technology, an important manifestation of the development of modern agriculture towards intelligence and precision, and has great application and promotion value. [Progress] Laser weeding is currently a research hotspot for scholars to develop and study key technologies and equipment for smart agriculture, and has achieved a series of significant results, greatly promoting the promotion and application of intelligent laser weeding robots in the field. Laser weed control technology achieves precise weed control through thermal, photochemical, and photodynamic effects. In this article, the research background of laser weeding was introduced, its key technologies, operation system and equipment were discussed in details, covering aspects such as operating principles, system architecture, seedling, weed recognition and localization, robot navigation and path planning, as well as actuator control technologies. Then, based on the current research status of laser weeding robots, the existing problems and development trends of intelligent laser weeding robots were prospected. [Conclusion and Prospect] Based on the different field grass conditions in different regions, a large number of indoor and outdoor experiments on laser weed control should be carried out in the future to further verify the technical effectiveness and feasibility of laser field weed control, providing support for the research and application of laser weed control equipment technology. Despite facing challenges such as high costs and poor environmental adaptability, with the integration of technologies such as artificial intelligence and the Internet of Things, as well as policy support, laser weeding is expected to become an important support for sustainable agricultural development.

Key words: laser weeding, technical principles, intelligent system, identify and locate, execution control, laser weeding robot

CLC Number:

YU Zhongyi, WANG Hongyu, HE Xiongkui, ZHAO Lei, WANG Yuanyuan, SUN Hai. Key Technologies and Prospects of Laser Weeding Robots[J]. Smart Agriculture, doi: 10.12133/j.smartag.SA202410031.

Figures/Tables 15

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Table 1

Table 2

Classification， advantages and disadvantages of field weed location technology

杂草定位技术	原理	优点	缺点
静态定位	依赖外部基准或预先部署的基础设施（如卫星信号、固定标志物或物理轨道）实现杂草位置的精准确定，其核心是利用预先建立的坐标系统或基础设施完成绝对或相对定位	定位精度较高（厘米级），无需复杂环境建模，系统成本较低，抗干扰能力较强等	依赖卫星信号或固定基础，环境适应性差，动态障碍物处理能力弱，路径灵活性受限等
自主定位	通过多模态传感器实时感知环境，结合SLAM（Simultaneous Localization and Mapping）算法和惯性导航，在无需外部基准的情况下动态构建地图并估计自身位置	无需外部基础设施，适应复杂动态环境，路径规划灵活，具备障碍物规避能力等	计算资源需求高，存在累积误差（需定期校准），复杂场景下精度下降（如杂草遮挡），系统成本较高等
双目视觉定位	基于计算机的模仿人类双眼的视觉系统，通过使用两个摄像头从不同角度获取同一物体的图像，来计算物体在三维空间中的位置和姿态，包括图像获取、特征提取、立体匹配和深度计算等	非接触式测量，定位精度较高，获取三维结构、视觉信息全面，实时性较好，尤其在机器人实时避障、动态目标跟踪等方面	对环境要求较高，定位精度易受影响，视场范围受限，计算量大，系统标定复杂等
结构光定位	一种常用的三维视觉测量技术，通过向物体表面投射特定的结构光图案，然后分析反射光来获取物体的三维信息，包括结构光投射、图像采集、分析及解码	测量精度高、速度快，可同时获取区域三维模型信息，减少测量误差，对环境光干扰抵抗力较好	对物体表面材质要求高，测量范围有限，系统复杂且成本高，不适用于动态测量

Table 2

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杂草识别技术	原理	优点	缺点
机器视觉技术	通过实时采集、处理、分析图像完成杂草和作物的识别和定位，可结合人工智能、杂草生物学、形态学特征进行识别和管理	可进行实时识别杂草图像，作业精度高、灵活性强、无接触识别且成本低，符合激光除草要求	采集的信息易受环境、机具影响，数据采集样本多，对激光除草设备稳定性要求高
光谱分析技术	一定光谱波段内利用农田作物、杂草、土壤等背景产生的电磁辐射反射率不同进行识别	识别迅速，不会对农田环境造成污染、破坏	光谱在农田作业时易受光照影响，波段识别精度低、易受干扰，激光除草精度不高
遥感识别技术	运用遥感图像进行杂草识别的技术，通过向靶标发射电磁波、红外线、可见光等并根据反射的作物、杂草位置信息进行判断	测量范围广，能够快速识别田间杂草	遥感图像分辨率不高，只能识别个体较大的杂草，激光除草识别率低，无法准确识别定位杂草
激光传感技术	通过X-射线、激光对射传感器等	成本低、操作方便、系统简单	精度低、受作物杂草的大小密度影响，难以做到激光精准除草