파레트가 다단 적재된 실내 환경에서의 지게차 포킹 자동화 알고리즘
Folklift forking automation algorithm in an indoor environment where pallets are stacked in multiple stages
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초록
물류 산업이 성장함에 따라 소형 창고는 수작업과 예산 제약으로 인해 비효율성에 직면하고 있다. 지게차는 대형 작업에서 필수적이지만, 팔레트 슬롯에 포크를 정확히 삽입하는 등의 정밀한 작업에는 여전히 사람의 개입이 필요하다. 이 논문은 RGB-D 카메라와 YOLOv5 모델을 사용하여 다단계 팔레트 적재에서 지게차 안내와 포크 작업을 자동화하는 알고리즘을 제안한다. 이 방법은 실시간으로 팔레트를 감지하고, 쌓여 있는 팔레트 배열 중에서 정확하게 선택할 수 있게 한다. 시스템은 초점 거리 관계를 계산하여 지게차와 팔레트 사이의 거리를 측정하고, 포크 삽입을 위한 정확한 위치를 계산한 후 지게차의 움직임을 바닥 수준과 다단계 적재 작업에 맞게 조정한다. 테스트 결과, 시스템은 효율성을 크게 향상시켰으며, 공간이 제한된 소형 창고에 적합한 비용 효율적인 자동화 솔루션을 제공한다.
Abstract
As the logistics industry grows, small warehouses face inefficiencies due to manual labor and budget constraints. Forklifts are vital for large tasks, but precise actions like inserting forks into pallet slots still require human input. This thesis presents an algorithm to automate forklift guidance and forking in multi-stage pallet stacking using an RGB-D camera and YOLOv5. Our approach allows real-time pallet detection and precise selection from stacked arrays. By calculating focal length relationships, the system measures the distance for accurate fork insertion and adjusts movement for both floor-level and multi-stage stacking. Tests show improved efficiency, offering a cost-effective automation solution for small warehouses.
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