• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1701-1704
• /
• 2005

We developed an machine vision method for navigation control of a traveling automatic guided vehicle(AGV) on desired trajectory with guided marks. The formulated EDF accumulates the edge magnitude for edge directions. The EDF has distinctive peak points at the vicinity of trajectory directions due to the directional and the positional continuities of desired trajectory. Examining the EDF by its shape parameters of the local maxima and symmetry axis results in identifying whether or not change in traveling direction of an AGV has occurred. Simulation results show that the presented method is useful for navigation control of AGV.

• Journal of the Institute of Convergence Signal Processing
• /
• v.22 no.2
• /
• pp.79-84
• /
• 2021

The most important device of the AGV is the guide sensor, and the typical function of this sensor is high accuracy and extraction of the road. If the accuracy of the guide sensor is low or the sensor device is extracted the wrong track, this causes the problems such as the AGV collision, track-out, the load falling due to AGV swing. In order to improve these problems, this study is proposed a signal processing method of the guide sensor based on multi-maskings and the center of gravity method, and evaluated its performance. As a result, the proposed method showed that the mean error of absolute value is 2.32[mm] and it showed performance improvement of 27[%] than the center of gravity method of existence. Therefore, when the proposed signal processing method is applied, It is thought that the posture control and driving stability of the AGV will be improved.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.8C
• /
• pp.721-730
• /
• 2012

In this paper the problem of a moving control of an automatic guided vehicle(AGV) which transports a dead body to a designated cinerator safely in a crematorium, an special indoor environment, will be discussed. Since a method of burying guided lines in the floor is not proper to such an environment, a method of moving control of an AGV based on infrared ray sensors is now proposed. With this approach, the AGV emits infrared ray to the landmarks adheres to the ceiling to find a moving direction and then moves that direction by recognizing them. One of the typical problems for this method is that dead zone and/or overlapping zone may exist when the landmarks are deployed. To resolve this problem, an algorithm of recognizing double landmarks at each time is applied to minimize occurrences of sensing error. In addition, at the turning area to entering the designated cinerator, to fit an AGV with the entrance of the designated cinerator, an algorithm of controlling the velocity of both the inner and outer wheel of it. The functional correctness of our proposed algorithm has been verified by using a prototype vehicle. Our real AGV system has been applied to a crematorium and it moves automatically within an allowable range of location error.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2004.05a
• /
• pp.275-275
• /
• 2004

현재 국가 간의 경쟁력 확보를 위하여 자동화 기술의 개발을 통한 무인화ㆍ자동화를 실현함으로써 물류비용 및 인건비의 절감을 위한 노력에 많은 투자가 이루어지고 있는 실정이다 FMS를 구축하기 위해서는 AGV는 반드시 필요한 운송 장치로 현재 많은 제품들이 생산되어 현장에서 사용되고 있다. 현재 AGV는 바닥에 설치되어 있는 주행라인을 따라서 이동하는 방식이 가장 많이 사용되고 있으며, 주행라인 검출 방식으로 말이 사용되고 있는 전자유도 방식은 설비비용이 말이 들고 경로 수정이 어렵다는 문제점을 가지고 있다.(중략)

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.20 no.43
• /
• pp.287-297
• /
• 1997

This research is concerned with operation control problem for an automated manufacturing system which consists of two machine centers and a single automatic guided vehicle. The objective is to develop and evaluate heuristic scheduling procedures that minimize maximum completion time to be included travel time of AGV. A new heuristic algorithm is proposed and a numerical example illustrates the proposed algorithm. The heuristic algorithm is implemented for various cases by SLAM II. The results show that the proposed algorithm provides better solutions than the previous algorithms.

• The Journal of Korea Robotics Society
• /
• v.8 no.1
• /
• pp.29-36
• /
• 2013

This paper presents a sensitivity optimization of a MEMS (microelectromechanical systems) gyroscope for a magnet-gyro system. The magnet-gyro system, which is a guidance system for a AGV (automatic or automated guided vehicle), uses a magnet positioning system and a yaw gyroscope. The magnet positioning system measures magnetism of a cylindrical magnet embedded on the floor, and AGV is guided by the motion direction angle calculated with the measured magnetism. If the magnet positioning system does not measure the magnetism, the AGV is guided by using angular velocity measured with the gyroscope. The gyroscope used for the magnet-gyro system is usually MEMS type. Because the MEMS gyroscope is made from the process technology in semiconductor device fabrication, it has small size, low-power and low price. However, the MEMS gyroscope has drift phenomenon caused by noise and calculation error. Precision ADC (analog to digital converter) and accurate sensitivity are needed to minimize the drift phenomenon. Therefore, this paper proposes the method of the sensitivity optimization of the MEMS gyroscope using DEAS (dynamic encoding algorithm for searches). For experiment, we used the AGV mounted with a laser navigation system which is able to measure accurate position of the AGV and compared result by the sensitivity value calculated by the proposed method with result by the sensitivity in specification of the MEMS gyroscope. In experimental results, we verified that the sensitivity value through the proposed method can calculate more accurate motion direction angle of the AGV.

• Proceedings of the KSME Conference
• /
• 2004.04a
• /
• pp.1076-1081
• /
• 2004

In this study, we have developed the simulation tool in order to investigate driving trajectory of AGV for container transport. AGV for container transport is different from the indoor AGV in that it is a large size structure at being loaded the weight of 40 ton. And AGV for container transport is applied to front wheel steering, rear wheel steering, all wheel steering, and crap steering. Therefore, we have developed the simulation tool considering dynamic problems and center of turning in accordance with four way of steering modes. Throughout some computer simulations, we have confirmed that this tool is useful to analysis dynamic problems and to calculate minimum radius of turning for large size vehicles.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2004.10a
• /
• pp.454-457
• /
• 2004

AGV for FMS must be detected an obstacle. Therefore, many studies have been advanced, and recently, the ultra sonic sensor is used for this. However, the new method has to be developed because the ultra-sonic-sensor has many problems as a noise in factory, an directional error and detection of the obstacle size. So, we study the fast stereo vision system that can give more information to obstacles for intelligent AGV system. For this, the simulated AGV system was made with two CCD cameras in front to get the stereo images, and the threshold process by color information (intensity and chromaticity) and structure stereo matching method were constructed.

• Proceedings of the KIEE Conference
• /
• 2002.07d
• /
• pp.2337-2340
• /
• 2002

This paper presents the method of AGV(Automatic guided vehicle)'s moving environment(plane, corner, edge) recognition using SONAR sensor configuration. As for the SONAR sensor, the Crosstalk effect has been generally considered as an inevitable noisy phenomenon in the indoor environment. However, this effect can be used as a clue for classifying and localizing targets in the indoor environment if those can be controlled and used well. EERUF(error eliminate rapid ultrasonic firing) is a method for firing multiple ultrasonic sensors in mobile robot application and multi-echo mode of POLARIOD Device can reduce the Crosstalk effect. Here, Crosstalk effect was reduced using EERUF and applied to the AGV with a simple wall-following algorithm in the indoor environment. This method was tesed by a typical AGV with multi SONAR sensors in the laboratory environment.

• International Journal of Industrial Entomology and Biomaterials
• /
• v.47 no.2
• /
• pp.79-89
• /
• 2023

This paper is about the development results of an automatic silkworm breeding system to reduce labor and time by automatically performing the works for silkworm droppings changing and feed its food. It consists of an automatic guided vehicle and a processing unit. The automatic guided vehicle transports a silkworm dropping changing frame mounted on a silkworm tray stand, and the processing unit takes over the dropping changing frame on it, removes excrement contained the droppings changing frame and feeds silkworm food. In the case of the current silkworm farming, because the breeding period for large silkworms (4 to 5 stage) is short to 14 days and the supply of mulberry leaves takes 98% of the total amount of mulberry leaves needed for breeding silkworms at this time, labor concentration is intensive, and all breeding works depends on manpower. Therefore, it was difficult to breed large silkworms on a large scale. Moreover, silkworms are bred by adding Silkworm bed (Seop) and mulberry in the silkworm tray, and their droppings changing is to separate silkworms and excrement by moving silkworm trays one by one, and the production cost increases due to the high-cost manpower for silkworm breeding. To solve this problem, technology for automating silkworm breeding has also been developed. However, there is still a limitation that silkworm feeding and droppings changing works are not suitable for mass breeding because a lot of labor and time are spent depending on manual work. Therefore, a new silkworm breeding system for breeding silkworm automatically is needed and so we developed an Automatic Silkworm Breeding System applying the droppings change frame, the inverting unit, the feeding silkworm food device and automatic guided vehicle.