基于改进YOLOv7的油茶果采收机器人树干检测方法
树干检测与识别是油茶果采收机器人的关键技术之一。传统的油茶果采收机树干检测方法主要依赖采收操作员的视觉判断,然而这样存在较大的识别误差和采收振动点错误定位的问题。基于视觉感知的树干检测与识别能够帮助油茶果采收机器人在非结构化环境中准确高效地检测和定位振动或采摘点。本文提出了一种基于改进 YOLO v7 网络的油茶果树干检测与识别方法。首先,在 YOLOv7 的主干层中添加了注意机制模块,以增强识别算法对树干的特征提取,从而使识别网络更专注于目标物…查看全部>>
Trunk recognition is a critical technology for Camellia oleifera fruit harvesting robots,as it enables accurate and efficient detection and localization of vibration or picking points in unstructured natural environments.Traditional trunk detection methods heavily rely on the visual judgment of robot operators,resulting in significant errors and incorrect vibration point identification.In this paper,we propose a new method based on an improved YOLOv7 network…查看全部>>
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