• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.4
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• pp.113-118
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• 2017

As the demand for industrial robots and Automated Guided Vehicles (AGVs) increases, higher performance is also required from them. Fuzzy controllers, as part of an intelligent control system, are a direct control method that leverages human knowledge and experience to easily control highly nonlinear, uncertain, and complex systems. This paper uses a $LabVIEW^{(R)}-based$ fuzzy controller with gain scheduling to demonstrate better performance than one could obtain with a fuzzy controller alone. First, the work area was set based on forward kinematics and inverse kinematics programs. Next, $LabVIEW^{(R)}$ was used to configure the fuzzy controller and perform the gain scheduling. Finally, the proposed fuzzy gain scheduling controller was compared with to controllers without gain scheduling.

• Journal of Digital Contents Society
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• v.5 no.1
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• pp.35-40
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• 2004

Today`s education is in the 7th education curriculum. But, there is nothing that can be used in the classroom as a tool for education supplement. Easylab is a GUI-programing tool for students who not good at using computers. EasyLab is used in the classroom as a kind of tool to give a rise to ingenuity and creation which need at present education curriculum. When use it, first, learners think of programming-ideas, then program through icon-based software-EasyLab. After programing, the leaner can see the result directly thorough the programing code which are delivered by EasyRobot. So, leaner can study and discuss with the robot`s result. If, the result is incorrect, the robot will do a feedback as a kind of rule. One of the EasyLab`s specific property is that consisted icon-based flow-chart model. And leaner can practice with the robot that have input and output sense.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.6
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• pp.55-62
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• 2017

This paper aims to realize additional axes, which increase the processing efficiency of a robot by controlling in harmful environments. Ultimately, this is to create time and energy savings in industrial sites with 6-axis articulated welding robots (RS2). Using $RecurDyn^{(R)}$ a simulation technique is applied. The motion paths of the welding rod are compared for two cases in order to verify the necessity of the additional axes: 1) when there are no additional axes and 2) when there are additional axes during welding using the RS2. For this purpose, the angle variations of the RS2 axes required for the simulation are compared, on the assumption that each of the four points of the welding bed installed on the additional axes of the welding rod in $Solidworks^{(R)}$ is point-welded. Then, actual additional axes equipment is grafted on to the RS2 and the process times compared using $LabVIEW^{(R)}$.