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물류센터 관리자의 조직 내 관계수행 능력이 물류센터 성과에 미치는 영향 연구
유헌종 ( Heonjong Yoo ),안우철 ( Woochul Ahn ),안승범 ( Seungbum Ahn ) 한국로지스틱스학회 2015 로지스틱스연구 Vol.23 No.2
Logistics centers play an important role in the SCM network. There are tangible and intangible assets that are widely considered as suitable variables for measuring performance of logistics centers. However, few confirmatory research have been conducted identifying the relationship between the intangible assets and the performance of logistics centers. Thus, this paper examines the impact of managers`` interorganizational relationship ability on the performance of logistics centers. Based on the sample of 90 professionals in Korea, it shows that intellectual stimulation, commitment to growth, communication, and trust had positive effects on working lead time. Furthermore, individual consideration had a positive impact on perfect order fulfillment. The results also identified that community building had a positive impact on the sales revenue. In conclusion, this study clearly identified that positive relationship building in the managerial level employees can have a positive impact on the overall performance of logistics centers.
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안승범 ( Seung-bum Ahn ),유헌종 ( Heonjong Yoo ) 한국로지스틱스학회 2017 로지스틱스연구 Vol.25 No.1
This study aims to analyze the differences of financial efficient gap in logistics industry by different types: second-party logistics company, third-party logistics company, large sized logistics company, and small & medium sized logistics company. Logistics companies were divided by the internal transaction ratio and sales account. Financial efficiency index consists of six variables (GRTA, GRS, OIS, NITA, TAT, and SET). Two-sample Kolmogorov-Smirnov test was applied to assess the differences of efficiency gap by different types of company. The results demontrate that financial efficiency gap is not significant by company type and scale.
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상태 흐름 방법을 기반으로 실내 환경에서 외발 자전거 형 이동 로봇을 위한 경로 추종 플랫폼 개발
첸티안 ( Tean Chen ),유헌종 ( Heonjong Yoo ),이경환 ( Kyeonghwan Lee ) 한국농업기계학회 2020 한국농업기계학회 학술발표논문집 Vol.25 No.2
Localization is one of the important method for autonomous indoor robots to recognize it’s own position. In general, navigation of mobile robots is conducted using camera, Lider and GPS. But in case of indoor environment, GPS is unavailable. In this presentation, an autonomous indoor mobile robot, that is, a shuttle robot used a state flow method via ROS network: MATLAB and Linux high-level computers, IMU sensor, and then was able to obtain the cartesian coordinate information of the unicycle type mobile robot. After setting the pre-determined time based on the length of the path in the State Flow block, a path planning which is able to execute the work effectively is established using state flow algorithm. The state flow block produces time-series data sets which represents linear and angular velocities signals. Depending on the numerical values of the signal, the left and right motor rotational speed should be calculated through mobile robot forward kinematics. Several cases are considered: Case I) indicated the linear velocity is set positive certain value, and angular velocity is zero, so that the corresponding mobile robot moves forward. Case II) says that the linear velocity is set positive certain value and angular velocity is set positive certain value, which means the mobile robot turns right. Case III) says that the linear velocity is set positive certain value and angular velocity is set negative certain value, which means the corresponding mobile robot turns left. Case IV) says that the linear velocity is set negative certain value and angular velocity is set zero, which indicates the mobile robot moves backward. The effectiveness of the methods is demonstrated through desktop based developed indoor mobile robot’s control results.
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첸티안 ( Tean Chen ),조철현 ( Jo Chulhyun ),유헌종 ( Heonjong Yoo ),이경환 ( Kyeonghwan Lee ) 한국농업기계학회 2021 한국농업기계학회 학술발표논문집 Vol.26 No.1
In this presentation, the state flow method is utilized for path following indoor environment. Here, the novel voice recognition part is incorporated into path tracking problem using TCPIP communication. The two path following scenario was designed, and TCPIP receive block receives ASCII code from Android program. If the ASCII value is bigger than threshold value we set in the TCPIP receive block, the block itself chooses path 1, otherwise the block chooses path 2 in the real-time implementation. In order to implement the voice recognition based platform control, the Android program, MATLAB/SIMULINK program, Linux system are connected through ROS (Robot operating system) node connection. To summarize that, nodes are composed of three parts: the Android program, Linux system, MATLAB/SIMULINK program.
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첸티안 ( Tean Chen ),조철현 ( Jo Chulhyun ),파블러 ( Pablo Vela ),유헌종 ( Heonjong Yoo ),이경환 ( Kyeonghwan Lee ) 한국농업기계학회 2021 한국농업기계학회 학술발표논문집 Vol.26 No.2
In an agricultural indoor environment like a greenhouse, it is hard to utilize GPS sensor for estimating mobile robot position. So odometry sensor i.g. encoder is needed for indoor agricultural robot localization. In a structured agricultural indoor environment, simultaneous localization and mapping method using multi-sensors such as Lidar, IMU, encoder to find a destination can be inefficient. we propose that encoder-based localization method based on a pre-built indoor environment map for efficient navigation of a 2-wheel agricultural indoor mobile robot. First, we constructed a 2D indoor map using Lidar and IMU data, and in the constructed map, for effective localization of the mobile robot, we divided the free space that the indoor mobile robot can navigate and the obstacles that interfere with the robot's moving in advance. And then to estimate the robot localization we adopt odometer increment model using encoder measurements of the indoor mobile robot. In order to evaluate the localization accuracy performance of our proposed method, we compared with the localization performance of the existing SLAM algorithms- LOAM, LeGo LOAM, A LOAM- for the position accuracy and odometry measurement accuracy with comparison to the position of the pre-built map. The position accuracy and odometry prediction accuracy of our proposed algorithm were evaluated as the average of 96.0% and 97.2% respectively. In the future, we will conduct further experiments in real agricultural indoor environments such as greenhouses.
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첸티안 ( Tean Chen ),조철현 ( Jo Chulhyun ),파블러 ( Pablo Vela ),유헌종 ( Heonjong Yoo ),이경환 ( Kyeonghwan Lee ) 한국농업기계학회 2022 한국농업기계학회 학술발표논문집 Vol.27 No.1
Accurate shuttle vehicle localization in the indoor environment on a precise map enables the mobile robot to estimate its position and orientation while moving in the indoor environment more efficiently. Trajectory tracking control is one of the fundamental techniques influencing a mobile robot's autonomous driving performance. MATLAB and Linux are high-level computers to equip the Inertial Measurement Unit (IMU), Velodyne VLP-16 channels LiDAR, and Encoder Sensors with the mobile robot platform. The mobile robot controls using a Robot Operating System (ROS) enabled robot, setup parameters for the differential wheels, and visualizes sensor data in a ROS robot visualization tool. In this paper, our model presents a new path following a method that integrates the pure pursuit algorithm and the state flow algorithm using the ROS Simulink model. The path following algorithm that performs autonomous waypoint navigation and obstacle avoidance method successfully localized and tested indoor environment. The accuracy improvement is demonstrated through several experimental results.
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