Horticultural tasks such as pruning and selective harvesting are labor intensive and horticultural staff are hard to find. Automating these tasks is challenging due to the semi-structured greenhouse workspaces, changing environmental conditions such as lighting, dense plant growth with many occlusions, and the need for gentle manipulation of non-rigid plant organs. In this work, we present the three-armed system HortiBot, with two arms for manipulation and a third arm as an articulated head for active perception using stereo cameras. Its perception system detects not only peppers, but also peduncles and stems in real time, and performs online data association to build a world model of pepper plants. Collision-aware online trajectory generation allows all three arms to safely track their respective targets for observation, grasping, and cutting. We integrated perception and manipulation to perform selective harvesting of peppers and evaluated the system in lab experiments. Using active perception coupled with end-effector force torque sensing for compliant manipulation, HortiBot achieves high success rates in our indoor pepper plant mock-up.

翻译：修剪与选择性采摘等园艺任务劳动强度大，且园艺劳动力日益短缺。由于温室工作空间呈半结构化、光照等环境条件不断变化、植物生长密集导致大量遮挡，以及需要对非刚性植物器官进行轻柔操作，实现这些任务的自动化颇具挑战。本研究提出三臂系统HortiBot，其中两臂用于操作，第三臂作为配备立体相机的铰接头部进行主动感知。其感知系统不仅能实时检测甜椒，还能识别果梗与茎干，并通过在线数据关联构建椒类植物的世界模型。具备碰撞感知的在线轨迹生成技术使得三臂能安全追踪各自目标，分别执行观察、抓取和切割任务。我们将感知与操作模块集成，实现了甜椒的选择性采摘，并在实验室环境中对系统进行了评估。通过结合主动感知与末端执行器力扭矩传感的顺应性操作，HortiBot在室内甜椒植株模拟场景中取得了较高的成功率。