Robotic apple harvesting offers a promising solution to labor shortages in commercial orchards, but low throughput and poor performance in orchard environments hinder its commercial adoption. This paper presents a modular dual-arm apple harvesting robot that uses a vertically stacked arms to enable simultaneous operation in the upper and lower zones of a single tree, simplifying platform positioning from multi-tree lateral repositioning to single-tree stops. Compared to our prior horizontal dual-arm system, the platform integrates 5 advances: (1)a foundation-model-based perception pipeline combining Grounding-DINO and EfficientViT-SAM for robust fruit localization in unstructured outdoor environments; (2)7th-order jerk-bounded trajectory generation paired with a Control Barrier Function safety filter to achieve fast yet safe arm motions; (3)a linear sweep harvesting strategy with a 10cm approach buffer and rotational detachment that improves picking reliability; (4)a temporal-logic-based dual-arm coordination policy with vision-arm async scheduling that maximizes usage of a shared vacuum source; and (5)field validation in 2 commercial orchards covering different apple varieties and tree architectures during the 2025 harvest season. Across the 1738 arm cycles collected in these field trials, the system achieved an 80.0% per-attempt success rate and a mean per-arm cycle time of 7.53s. Fruit damage assessments confirmed that 91.2% of robotically harvested fruit retained the highest USDA grade (Extra Fancy), with bruise rates between 2.4% and 4.9%. With further improvements in the picking cycle time and handling of heavy foliage occlusions, this new modular robot design holds promise for commercial harvesting of apples.

翻译：机器人苹果采摘为商业果园劳动力短缺问题提供了有前景的解决方案，但在果园环境下吞吐量低且性能不佳阻碍了其商业化应用。本文提出了一种模块化双臂苹果采摘机器人，采用垂直堆叠的机械臂设计，使其能够同时在单棵树的上下区域作业，从而将平台定位从多树横向重新定位简化为单棵树停靠。与先前水平双臂系统相比，该平台集成了5项改进：(1)基于基础模型的感知流水线，结合Grounding-DINO和EfficientViT-SAM，实现非结构化户外环境下的稳健果实定位；(2)结合控制屏障函数安全滤波器的七阶加加速度有界轨迹生成，实现快速且安全的机械臂运动；(3)采用线性扫描采摘策略，配备10厘米接近缓冲与旋转脱落方式，提高采摘可靠性；(4)基于时序逻辑的双臂协同策略与视觉-机械臂异步调度，最大化共享真空源的使用效率；(5)在2025年收获季于涵盖不同苹果品种与树体结构的两个商业果园中进行现场验证。在田间试验收集的1738个机械臂循环中，系统实现了80.0%的单次尝试成功率，平均单臂循环时间为7.53秒。果实损伤评估证实，91.2%的机器人采摘果实保留了美国农业部最高等级（特级），瘀伤率介于2.4%至4.9%之间。通过进一步缩短采摘循环时间并改善枝叶严重遮挡的处理能力，这种新型模块化机器人设计有望实现苹果的商业化采摘。