针对密集大棚环境，设计了双相机协同的抓取系统，提升番茄采摘精度与效率。
Precision Harvesting in Cluttered Environments: Integrating End Effector Design with Dual Camera Perception
- 双相机闭环视觉反馈，结合末端执行器设计实现精准定位
- 在高架大棚中平均10.98秒采摘85.0%的樱桃番茄
- 适合复杂农田场景的机器人采摘任务，可推广至其他小果作物
由于特色农产品行业面临劳动力短缺，亟需机器人自动化以提高农业效率与产能。以往的抓取系统在无遮挡、结构化环境中表现良好，但在更紧凑、杂乱的高架大棚环境中，传统大体积系统与夹爪难以适用。本文提出一种新型协同设计框架，融合全局检测相机与局部眼在手上相机，通过闭环视觉反馈实现对小型果实的精确位姿估计，并具备可靠的误差处理能力。田间实测表明，该系统在高架大棚环境下平均可在10.98秒内完成85.0%樱桃番茄的采摘任务。
原文摘要 · Abstract (English)
Due to labor shortages in specialty crop industries, a need for robotic automation to increase agricultural efficiency and productivity has arisen. Previous manipulation systems perform well in harvesting in uncluttered and structured environments. High tunnel environments are more compact and cluttered in nature, requiring a rethinking of the large form factor systems and grippers. We propose a novel codesigned framework incorporating a global detection camera and a local eye-in-hand camera that demonstrates precise localization of small fruits via closed-loop visual feedback and reliable error handling. Field experiments in high tunnels show our system can reach an average of 85.0\% of cherry tomato fruit in 10.98s on average.
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