MARTS：用于温室番茄病株靶向喷施的模块化农业机器人
MARTS: A Modular Agricultural Robot for Targeted Spraying of Diseased Tomato Plants in Greenhouses
AI总结：
本研究提出低成本农业机器人MARTS，集成多硬件与ROS管道实现温室番茄病叶靶向喷施，经仿真与实地测试，其靶向成功率92.4%，农药用量减71%，成本仅为同类系统的1/6至1/10。
摘要：
在温室番茄生产中，广谱喷施仍是病害防控的主流方法，但该方法会同时处理健康组织与患病组织，使工人暴露于有害气溶胶中，且依赖操作人员的技能。本文提出MARTS（Modular Agricultural Robot for Targeted Spraying，用于靶向喷施的模块化农业机器人），这是一种低成本机器人平台，可在商业温室中实现从植物级病害检测到叶片局部喷施的闭环。MARTS集成了Clearpath Husky A200移动底盘、UR5机械臂、围绕单个12V微型隔膜泵构建的新型模块化喷施末端执行器，以及腕部安装的Intel RealSense D435 RGB-D相机。病害检测复用了我们此前发表的番茄叶片病害视觉语言模型（TLDVLM；基于Grounding DINO、SAM-2和LoRA微调的BLIP-2，在10类病害上准确率达97.27%）；本研究聚焦于驱动、控制与系统集成。ROS管道将检测结果转换为3D目标，利用拟合的叶片法向量生成距目标120mm的避障喷嘴位姿，并根据病斑面积调整泵的脉冲持续时间。对水敏纸的校准显示脉冲体积呈线性关系（R²=0.994）。在MuJoCo仿真中，自适应底盘重定位策略实现了18个航路点的100%覆盖，最大姿态误差为1.1度。在阿联酋艾因的SILAL商业温室中，针对自然感染的樱桃番茄开展部署，MARTS在12次自主试验中处理了312片病叶，靶向成功率达92.4%，喷施中心平均误差为18.7mm，相邻叶片过喷率为6.1%，与广谱喷施相比农药用量减少71%。平均单叶处理周期为4.8秒，喷施子系统成本为412美元，比同类系统低6-10倍，表明在商用硬件上可实现精准的叶片级靶向喷施。
英文摘要：
Broadcast spraying remains the dominant method of disease control in greenhouse tomato production, yet it treats healthy and diseased tissue alike, exposes workers to hazardous aerosols, and depends on operator skill. This paper presents MARTS (Modular Agricultural Robot for Targeted Spraying), a low-cost robotic platform that closes the loop from plant-level disease detection to leaf-localised spray delivery in commercial greenhouses. MARTS integrates a Clearpath Husky A200 mobile base, a UR5 manipulator, a novel modular spraying end-effector built around a single 12 V micro-diaphragm pump, and a wrist-mounted Intel RealSense D435 RGB-D camera. Disease detection reuses our previously published Tomato Leaf Disease Vision Language Model (TLDVLM; Grounding DINO, SAM-2 and LoRA-tuned BLIP-2, 97.27% accuracy over 10 classes); this work focuses on actuation, control and system integration. A ROS pipeline lifts detections into 3D targets, generates collision-aware nozzle poses at a 120 mm stand-off using fitted leaf normals, and scales pump pulse duration to lesion area. Water-sensitive paper calibration showed a linear pulse-volume relationship (R^2 = 0.994). In MuJoCo simulation, an adaptive base-repositioning strategy achieved 100% coverage of 18 waypoints with a maximum orientation error of 1.1 deg. Deployed at the SILAL commercial greenhouse (Al Ain, UAE) on cherry tomatoes under natural infection, MARTS treated 312 diseased leaves in 12 autonomous trials with 92.4% targeting success, 18.7 mm mean spray-centre error, 6.1% adjacent-leaf overspray, and a 71% reduction in pesticide volume versus broadcast spraying. Mean cycle time was 4.8 s per leaf, and the spraying subsystem costs USD 412, 6-10x lower than comparable systems, showing that accurate leaf-level targeting is achievable on commodity hardware.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
