• 대한안전경영과학회지
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• 제25권1호
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• pp.15-21
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• 2023

In modern society, the delivery service market has grown explosively due to rapid changes in social structure and the recent COVID-19 pandemic. Therefore, various problems such as injury to workers and an increase in human accidents are occurring due to the loading and unloading of parcels. In order to solve this problem, domestic company n is developing a "robot-based cargo loading and unloading system". In developing a new technology system, quantitative reliability targets should be set for efficient operation and development. In this paper, reliability analysis was conducted through field data for the pneumatic gripper of the "robot-based cargo loading system". The reliability of the failure data was analyzed to estimate the distribution parameters and MTTF. Random data was derived for the probability of occurrence of a failure with the estimated value. By repeating the simulation to predict the number and year of failures according to the estimated parameters of the probability distribution, it was proposed as a method that reflects realistic probabilities rather than calculating with simple arithmetic using the average MTTF previously used in the field.

• International Journal of Internet, Broadcasting and Communication
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• 제14권1호
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• pp.85-94
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• 2022

Recently, consumers who prefer contactless consumption are increasing due to pandemic trends such as Corona 19. This is the driving force for developing the last mile-based logistics ecosystem centered on the online e-commerce market. Lastmile led to the continued development of the logistics industry, but increased the amount of cargo in urban area, and caused social problems such as overcrowding of logistics. The courier service in the logistics base area utilizes the process of visiting the delivery site directly because the courier must precede the loading work of the cargo in the truck for the delivery of the ordered product. Currently, it's carried out as automated logistics equipment such as conveyor belt in unloading or classification stage, but the automation system isn't applied, so the work efficiency is decreasing and the intensity of the courier worker's labor is increased. In particular, small-scale courier workers belonging to the sub-terminal unload at night at underdeveloped facilities outside the city center. Therefore, the productivity of the work is lowered and the risk of safety accidents is exposed, so robot-based loading technology is needed. In this paper, we have derived the top-level concept and requirements of robot-based loading system to increase the flexibility of logistics processing and to ensure the safety of courier drivers. We defined algorithms and motion concepts to increase the cargo loading efficiency of logistics sub-terminals through the requirements of end effector technology, which is important among concepts. Finally, the control technique was proposed to determine and position the load for design input development of the automatic conveyor system.

• International Journal of Internet, Broadcasting and Communication
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• 제13권4호
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• pp.90-96
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• 2021

The logistics market is continuously growing due to the development of technology and the growth of the online market. In addition, the social atmosphere that emphasizes non-face-to-face due to the pandemic situation is accelerating the growth of logistics. Delivery of goods ordered online requires delivery process through courier worker. In order for the courier worker to ship the product, the work of loading the product on the truck must be preceded. The accident caused by such delivery and loading work is increasing and it is emerging as a social problem. This study proposes a robot-based automated loading system to efficiently handle the increasing volume of courier service and to construct a more efficient and safe working environment by replacing the physical labor that was overloaded to courier workers. The proposed system replaces the loading of the courier worker and proposes the optimal loading function through the automation system.

• 로봇학회논문지
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• 제17권4호
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• pp.417-424
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• 2022

In this paper, the developed trunk cargo unloading automation system is introduced, and the RGB-D sensor-based box loading situation recognition method and unloading plan applied to this system are suggested. First of all, it is necessary to recognize the position of the box in a truck. To do this, we first apply CNN-based YOLO, which can recognize objects in RGB images in real-time. Then, the normal vector of the center of the box is obtained using the depth image to reduce misrecognition in parts other than the box, and the inner wall of the truck in an image is removed. And a method of classifying the layers of the boxes according to the distance using the recognized depth information of the boxes is suggested. Given the coordinates of the boxes on the nearest layer, a method of generating the optimal path to take out the boxes the fastest using this information is introduced. In addition, kinematic analysis is performed to move the conveyor to the position of the box to be taken out of the truck, and kinematic analysis is also performed to control the robot arm that takes out the boxes. Finally, the effectiveness of the developed system and algorithm through a test bed is proved.