딥러닝을 이용한 팔레트 위치 측정 시스템의 성능 개선에 관한 연구

다국어 초록 (Multilingual Abstract)

Recently, the logistics system environment is in the trend of unmanned and automated. In addition, most of the unmanned logistics systems have advanced technology that can identify the location by sensors and load or move goods without operator support or interference. And the unmanned logistics system requires a prerequisite that the pallet position is always in the correct position. However, since not all logistics processes can be automated, there are areas where this assumption does not apply. Various studies have been conducted to implement an unmanned automation system in these environments. Traditional vision-based image processing techniques have a fast processing speed, but there is a weak problem in the disturbance of images. On the other hand, the deep learning technique has a disadvantage in that the object extraction speed is slow due to the large amount of computation. Therefore, in this study, we proposed a method that can measure the exact position of the pallet by verifying the object at high speed while being strong against disturbance by appropriately utilizing the advantages of the two methods.

참고문헌 (Reference)

1 박세준, "무인 물류이송을 위한 위치인식센서 기반 지능형 이동로봇의 설계에 관한 연구" 한국정보기술학회 11 (11): 7-13, 2013

2 D. Lecking, "Variable Pallet Pick-Up for Automatic Guided Vehicles in Industrial Environments" 1169-1174, 2006

3 Gang Chen, "Pallet recognition and localization method for vision guided forklift" 1-4, 2012

4 Ihab S. Mohamed, "Detection, localisation and tracking of pallets using machine learning techniques and 2D range data" 32 : 8811-8828, 2019

5 L Baglivo, "Autonomous pallet localization and picking for industrial forklifts: a robust range and look method" 22 (22): 707-713, 2011

6 Shijun Wang, "Autonomous Pallet Localization and Picking for Industrial Forklifts Based on the Line Structured Light" 707-713, 2016

7 M. Seelinger, "Automatic Visual Guidance of a Forklift Engaging a Pallet" 54 (54): 026-1038, 2006

8 Ji-Youn Oh, "An Experimental Study of Pallet Recognition System Using Kinect Camera" 42 : 167-170, 2013

9 Jia-Liang Syu, "A computer vision assisted system for autonomous forklift vehicles in real factory environment" 76 (76): 18387-18407, 2016

10 Guang-zhao Cui, "A Robust Autonomous Mobile Forklift Pallet Recognition" 286-290, 2010

11 이태화, "3방향 레이블링과 면특성을 이용한 다단 팔레트 인식" 한국정보기술학회 17 (17): 87-94, 2019