基于空中双臂操作的视觉辅助牛油果采收
Vision-assisted Avocado Harvesting with Aerial Bimanual Manipulation
AI总结：
针对牛油果等作物地面采收效率低的问题，研究设计了搭载视觉感知与双臂系统的无人机，通过固定臂稳果梗、夹持臂旋转采收，经实验验证了各组件及整体系统的采收有效性。
摘要：
机器人果实采收在精准农业中具备提升采收效率的潜力。目前果实采收多采用地面移动机器人，但对于牛油果这类作物，仅从地面无法实现高效采收——原因在于地面环境非结构化、种植布局特殊，且果实位置较高难以触及。这类场景下，集成操作能力的空中机器人可为机器人采收开辟新路径。\n本文阐述了一款双臂无人机（UAV）的设计与实现，该无人机借助视觉感知与学习技术，可自主检测牛油果、抵达目标位置并完成采收。双臂系统包含一个夹持臂和一个固定臂，用于解决牛油果采收的一项核心挑战：牛油果被抓取后，旋转动作是将其从果梗上分离的最高效方式，但果梗可能储存弹性能量，阻碍牛油果采收。固定臂的作用是稳定果梗，使夹持臂能够完成采收。集成的视觉感知流程可实现牛油果检测及其位姿确定，位姿信息随后用于为双臂操作规划器确定目标点。研究开展了多项实验评估各组件的效能，并通过集成实验验证了整个系统的有效性。
英文摘要：
Robotic fruit harvesting holds potential in precision agriculture to improve harvesting efficiency. While ground mobile robots are mostly employed in fruit harvesting, certain crops, like avocado trees, cannot be harvested efficiently from the ground alone. This is because of unstructured ground and planting arrangement and high-to-reach fruits. In such cases, aerial robots integrated with manipulation capabilities can pave new ways in robotic harvesting. This paper outlines the design and implementation of a bimanual UAV that employs visual perception and learning to autonomously detect avocados, reach, and harvest them. The dual-arm system comprises a gripper and a fixer arm, to address a key challenge when harvesting avocados: once grasped, a rotational motion is the most efficient way to detach the avocado from the peduncle; however, the peduncle may store elastic energy preventing the avocado from being harvested. The fixer arm aims to stabilize the peduncle, allowing the gripper arm to harvest. The integrated visual perception process enables the detection of avocados and the determination of their pose; the latter is then used to determine target points for a bimanual manipulation planner. Several experiments are conducted to assess the efficacy of each component, and integrated experiments assess the effectiveness of the system.
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。
