YOLO기반의 객체인식을 통한 딸기 수확 로봇 시스템에 대한 연구
Abstract
Recently, interest in intelligent agricultural robots has surged due to the aging of rural workers, leading to active research on agricultural automation. We designed a strawberry harvesting robot that moves along a rail, equipped with a 3-axis linear actuator, an RGB-Depth camera for object detection, and a rotary gripper for branch cutting. Our research focused on developing algorithms for strawberry maturity classification using an AI vision system, calculating cutting points for fruit acquisition, and implementing these algorithms in a robot. A convolutional neural network based on YOLO was employed for object detection, and representation learning was used to determine the picking point with an ROI(Region Of Interest) image derived from object detection. Our strawberry harvesting robot system boasts an average harvesting success rate of 90% for ripe fruits.
Keywords:
Agricultural robot, RGB-depth camera, YOLO, Object detection, Strawberry harvestingReferences
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Master Course in the Department of Mechanical Engineering, Sogang University. His research interest is Robotics.
Email: seuungwon426@naver.com
Master Course in the Department of Mechanical Engineering, Sogang University. His research interest is Mobile robot, ROS.
Email: bggh9395@naver.com
Master in the Department of Mechanical Engineering, Sogang University. His research interest is Robotics, Mechanical Design, Machine Learning.
E-mail: kyk6230@naver.com
Research Professor in the Department of Mechanical Engineering, Sogang University. His research interests are Robot System and Control and Radiopharmaceutical Automatic Manufacturing System.
E-mail: griffon0@gmail.com
Professor in the Department of Mechanical Engineering, Sogang University. His research interests are Geometric Modeling and Computer aided Manufacturing and Design of Machine Tools and Medical Device Development and Manufacturing.
E-mail: cscam@sogang.ac.kr