基于视觉的快件自动分拣系统
Vision Based Picking System for Automatic Express Package Dispatching
摘要：
本文提出了一种基于视觉的机器人系统来处理自动快递包裹派送中的拣选问题。通过使用两个RealSense RGB-D摄像头和一个UR 10工业机器人，可以自动完成通常由人类完成的包裹调度任务。为了确定重叠的可变形物体的抓取点，我们改进了伯克利小组提出的采样算法，直接从深度图像生成抓取候选。为了实现包识别，集成了深度网络框架YOLO。设计了一种由双指夹持器和真空吸盘组成的多模态机器人手，用于处理不同类型的包装物。所有的技术已经集成在一个工作单元，模拟快递包裹调度场景的实际条件。通过对两个典型快递物品的实验，验证了该系统的有效性。
英文摘要：
This paper presents a vision based robotic system to handle the picking problem involved in automatic express package dispatching. By utilizing two RealSense RGB-D cameras and one UR10 industrial robot, package dispatching task which is usually done by human can be completed automatically. In order to determine grasp point for overlapped deformable objects, we improved the sampling algorithm proposed by the group in Berkeley to directly generate grasp candidate from depth images. For the purpose of package recognition, the deep network framework YOLO is integrated. We also designed a multi-modal robot hand composed of a two-fingered gripper and a vacuum suction cup to deal with different kinds of packages. All the technologies have been integrated in a work cell which simulates the practical conditions of an express package dispatching scenario. The proposed system is verified by experiments conducted for two typical express items.
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。
