无人机机械臂精准定位花蕊,实现无接触授粉。
An Aerial Manipulator for Perception-Driven Flower Targeting Toward Contactless Pollination in Vertical Farming

- 用RGBD感知+MPPI控制实现空中精准定位
- 实测末端执行器定位精度达厘米级
- 适合垂直农场无接触授粉系统研发
自然传粉昆虫减少给受控室内农业,特别是垂直农场带来重大挑战,因缺乏自然授粉。为此,本文提出一种用于感知驱动花蕊定位与接近的空中机械臂平台。系统集成机载RGBD感知、基于MPPI的PX4无人机控制及轻量2自由度机械臂,实现末端执行器精确定位。在MuJoCo仿真和无人机实验室中通过花蕊定位测试平台验证,结果表明飞行稳定,花蕊定位可靠,末端执行器定位精度达厘米级。仿真中控制器实现轨迹一致收敛与目标精准对齐;真实环境中框架支持受限空域下的稳定花蕊定位与执行器对准。验证了该平台作为未来无接触授粉系统的可靠载体与定位框架。当前研究聚焦于感知引导的目标定位,所开发平台为后续集成声学等非接触式花粉操作模块奠定基础。
原文摘要 · Abstract (English)
The decline of natural pollinators has created a major challenge for crop production in controlled indoor agriculture, particularly in vertical farming environments where natural insect pollination is absent. This motivates the development of robotic systems capable of performing precise flower targeting tasks while minimizing physical interference with delicate floral structures. This paper presents an aerial manipulator platform for perception driven flower detection, localization, and approach in vertical farming environments. The proposed system integrates onboard RGBD based perception, model predictive path integral (MPPI) based unmanned aerial vehicle (UAV) control on a PX4 platform, and a lightweight 2DoF manipulator for precise end effector positioning. The platform is evaluated in both MuJoCo simulation and UAV lab experiments using a flower targeting testbed. The experimental results demonstrate stable UAV flight, reliable flower localization, and centimeter level end effector positioning accuracy. In simulation, the proposed controller achieves consistent trajectory convergence and accurate target alignment. In the real world UAV lab environment, the integrated perception control manipulation framework enables stable flower targeted positioning and end effector alignment under constrained aerial operation. These results validate the proposed aerial manipulator as a robust robotic carrier and positioning framework for future contactless pollination systems. While the current study focuses on perception guided targeting and positioning, the developed platform provides a practical foundation for integrating advanced contactless end effectors, including acoustic based pollen manipulation modules, in future work.
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