• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.497-500
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• 1988

The multi-task operating system called HRMTOS (HUNDAI Robot Multi-task Operating System) was developed for concurrent execution. HRMTOS consists of condition interpreter, queue constructor, task scheduler. Condition interpreter checks the status and condition of request, queue constructor makes queue according to the checked result by condition interpreter, and task scheduler finds the task that will be urgently executed by priority of queue after pending the current excuting task. HRMTOS could execute teaching, playback, monitoring function of multi-robot and could be used more effectively than other robot controllers.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.49-60
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• 1999

This paper addresses a welding task sequencing for robot arc welding process planning. Although welding task sequencing is an essential step in the welding process planning, it has not been considered through a systematic approach, but it depends rather on empirical knowledge. Thus, an effective task sequencing for robot arc welding is required. Welding perations can be classified by the number of welding robots. Genetic algorithms are applied to tackle those welding task sequencing problems. A genetic algorithm for traveling salesman problem (TSP) is utilized to determine welding task sequencing for a MultiWeldline-SingleLayer problem. Further, welding task sequencing for multiWeldline-MultiLayer welding is investigated and appropriate genetic algorithms are introduced. A random key genetic algorithm is also proposed to solve multi-robot welding sequencing : MultiWeldline with multi robots. Finally, the genetic algorithm are implemented for the welding task sequencing of three dimensional weld plate assemblies. Robot welding operations conforming to the algorithms are simulated in graphic detail using a robot simulation software IGRIP.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.441-452
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• 2021

Federated learning provides an efficient integrated model for distributed data, allowing the local training of different data. Meanwhile, the goal of multi-task learning is to simultaneously establish models for multiple related tasks, and to obtain the underlying main structure. However, traditional federated multi-task learning models not only have strict requirements for the data distribution, but also demand large amounts of calculation and have slow convergence, which hindered their promotion in many fields. In our work, we apply the rank constraint on weight vectors of the multi-task learning model to adaptively adjust the task's similarity learning, according to the distribution of federal node data. The proposed model has a general framework for solving optimal solutions, which can be used to deal with various data types. Experiments show that our model has achieved the best results in different dataset. Notably, our model can still obtain stable results in datasets with large distribution differences. In addition, compared with traditional federated multi-task learning models, our algorithm is able to converge on a local optimal solution within limited training iterations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3566-3582
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• 2019

In intelligent warehouse picking system, the allocation of tasks has an important influence on the efficiency of the whole system because of the large number of robots and orders. The paper proposes a method to solve the task allocation problem that multi-robot task allocation problem is transformed into transportation problem to find a collision-free task allocation scheme and then improve the capability of task processing. The task time window and the power consumption of multi-robot (driving distance) are regarded as the utility function and the maximized utility function is the objective function. Then an integer programming formulation is constructed considering the number of task assignment on an agent according to their battery consumption restriction. The problem of task allocation is solved by table working method. Finally, simulation modeling of the methods based on table working method is carried out. Results show that the method has good performance and can improve the efficiency of the task execution.

• Design & Manufacturing
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• v.16 no.3
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• pp.1-8
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• 2022

In this study, an artificial neural network(ANN) was constructed to establish the relationship between process condition prameters and the qualities of the injection-molded product in the injection molding process. Six process parmeters were set as input parameter for ANN: melt temperature, mold temperature, injection speed, packing pressure, packing time, and cooling time. As output parameters, the mass, nominal diameter, and height of the injection-molded product were set. Two learning structures were applied to the ANN. The single-task learning, in which all output parameters are learned in correlation with each other, and the multi-task learning structure in which each output parameters is individually learned according to the characteristics, were constructed. As a result of constructing an artificial neural network with two learning structures and evaluating the prediction performance, it was confirmed that the predicted value of the ANN to which the multi-task learning structure was applied had a low RMSE compared with the single-task learning structure. In addition, when comparing the quality specifications of injection molded products with the prediction values of the ANN, it was confirmed that the ANN of the multi-task learning structure satisfies the quality specifications for all of the mass, diameter, and height.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.305-309
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• 2018

딥러닝에서 층을 공유하여 작업에 따라 변하지 않는 정보를 사용하는 multi-task learning이 다양한 자연어 처리 문제에 훌륭하게 사용되었다. 그렇지만 우리가 아는 한 공유 공간의 상태와 성능과의 관계를 조사한 연구는 없었다. 본 연구에서는 공유 공간과 task 의존 공간의 자질의 수와 오염 정도가 성능에 미치는 영향도 조사하여 공유 공간과 성능 관계에 대해서 탐구한다. 이 결과는 multi-task를 진행하는 실험에서 공유 공간의 역할과 성능의 관계를 밝혀서 시스템의 성능 향상에 도움이 될 것이다.

• Journal of the Korean Society of Safety
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• v.24 no.2
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• pp.76-82
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• 2009

The NIOSH lifting equation has been used as a dominant tool in evaluating the hazard levels of lifting tasks. Although it provides two different ways for each simple and complex lifting task, the NIOSH simple lifting equation is almost used for not only simple tasks but also complex tasks. However, most of lifting tasks in industries are in the form of complex lifting. Therefore some errors occur inevitably in the evaluation of complex lifting tasks. Among complex lifting tasks, a multi-stacking task is the most popular in lifting tasks. To compensate the error in the evaluation of multi-stacking tasks by using the NIOSH simple lifting equation, a set of calculations for finding LIs(Lifting Indices) was performed for the systematically varying multi-stacking tasks. Then a regression model which finds the equivalent height in simple lifting task for multi-stacking task was established. By using this model, multi-stacking tasks can be evaluated with less error. To validate this model, some real multi-stacking tasks were evaluated as examples.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.3
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• pp.215-220
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• 2021

As the role of robots expands, flexible task planning methods are attracting attention from various domains. Many task planning frameworks are introduced to efficiently work in a wide range of areas. In order to work well in a broad region with multiple robots, various communication conditions should be controlled by task planning frameworks. However, few methods are proposed. In this paper, we propose mission planning methods according to the communication status of robots. The proposed method was verified through experiments assuming different communication states with a multi-robot system.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.6 no.3
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• pp.112-118
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• 2007

Recently, the machine tools called multi-task machines, which mounted rotary axes on the table or spindle are used increasingly. Accordingly, multi-task machine tool takes a growing interest on the motion accuracy of feed drive system. In this study, measurement and diagnosis of motion errors ware attempted from circular pattern obtained by using DBB (Double ball bar) device. Those were obtained at both clockwise and counter clockwise motions in mutually perpendicularly intersecting three planes. The reliability of error measurement system for multi-task machine tool was verified by the direct test cutting.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.6 no.3
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• pp.31-37
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• 2007

Recently, the machine tools called multi-task machines, which mounted rotary axes on the table or spindle are used increasingly. Accordingly, multi-task machine tool takes a growing interest on the motion accuracy of feed drive system. In this study, measurement and diagnosis of motion errors ware attempted from circular pattern obtained by using DBB (Double ball bar) device. Those were obtained at both clockwise and counter clockwise motions in mutually perpendicularly intersecting three planes. The reliability of error measurement system for multi-task machine tool was verified by the direct test cutting.