双臂采摘机器人提升果园作业效率，实测成功率80%、损伤率低于5%。

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.