• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.720-723
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• 1997

This paper presents a cooperative control method for multiple robots. This method is based on local sensors. The proposed method integrates all information obtained by local perception through a set of sensors and generates commands without logical conflicts in designing control logic. To control multiple robots effectively, a global control strategy is proposed. These methods are constructed by using AND/OR logic and transition firing sequences in Petri nets. To evaluate these methods, the object-searching task is introduced. This task is to search an object like a box by two robots and consists of two sub-tasks, i.e., a wall tracking task and a robot tracking task. Simulation results for the object-searching task and the wall tracking task are presented to show the effectiveness of the method.

• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.127-132
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• 2016

For a practical mobile robot team such as carrying out a search and rescue mission in a disaster area, the localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a global positioning system (GPS) is unavailable. The proposed architecture supports localizing robots seamlessly by finding their relative locations while moving from a global outdoor environment to a local indoor position. The proposed schemes use a cooperative positioning system (CPS) based on the two-way ranging (TWR) technique. In the proposed TWR-based CPS, each non-localized mobile robot act as tag, and finds its position using bilateral range measurements of all localized mobile robots. The localized mobile robots act as anchors, and support the localization of mobile robots in the GPS-shadow region such as an indoor environment. As a tag localizes its position with anchors, the position error of the anchor propagates to the tag, and the position error of the tag accumulates the position errors of the anchor. To minimize the effect of error propagation, this paper suggests the new scheme of full-mesh based CPS for improving the position accuracy. The proposed schemes assuring localization were validated through experiment results.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.2
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• pp.288-294
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• 2009

The purpose of this study is manufacturing of monolithic housing for modularization of steering gear. Monolithic housing is difficult to weld with only rotation and linear motion. It is for this reason that housing of joining parts have a slope of 76.3 degrees. For this reason, welding trajectory was measured by the cooperative controled robot system, and then allowing for measured results, we developed the dedicated system. The developed system can be welded by using only 3 axises in contrast with robot system using 8 axises in housing welding. In addition, we applied CMT and laser welding device to dedicated system and as a result of experiment, sound bead and excellent roundness could be obtained.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.102-109
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• 1998

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment.For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows. When the environmental codintion changes, a robot select an appropriate beharior stategy. And its behavior stategy is stimulated and suppressed by other robot using communiation. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idotopic network hypothesis. And it is used for decision making of optimal swarm stragegy.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.205-211
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• 2024

Effective warehouse management requires advanced resource planning to optimize profits and space. Robots offer a promising solution, but their effectiveness relies on embedded artificial intelligence. Multi-agent reinforcement learning (MARL) enhances robot intelligence in these environments. This study explores various MARL algorithms using the Multi-Robot Warehouse Environment (RWARE) to determine their suitability for warehouse resource planning. Our findings show that cooperative MARL is essential for effective warehouse management. IA2C outperforms MAA2C and VDA2C on smaller maps, while VDA2C excels on larger maps. IA2C's decentralized approach, focusing on cooperation over collaboration, allows for higher reward collection in smaller environments. However, as map size increases, reward collection decreases due to the need for extensive exploration. This study highlights the importance of selecting the appropriate MARL algorithm based on the specific warehouse environment's requirements and scale.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.165-166
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• 2009

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.155.3-155
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• 2001

Researches of multi-robot system are active in these days. The most remarkable characteristic of multirobot system is that the robots work cooperatively and achieve the task which a single robot cannot do. It is essential to investigate number effect of multi-robot system. In this paper, we chose foraging task and investigated their behavior. At first, we investigated the foraging behavior in case that interaction range is Infinite. Secondly, we investigated the behavior in case that interaction range is finite. In both case, we find out there is an optimum interaction duration.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.332-336
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• 1992

We describe about the graphic simulation system which supports the determination of efficient multi-robot motions during cooperation. For the construction of the simulation software for multi-robot motions, two problems are presented. First problem is that all the robot motions must be determinded using both the desired object motions and the holonomic constraints with the object. To find the robot motions combined with the various object motion path, the robot motions are derived from the desired object path instead of a master robot path. Therefore robot motions can be easily modifiable with the various object motions. This type of motion determination is different from that of the master-slaves method using the master robot motions. The other is that the developments of robot application softwares need a heavy cost when the participated robots or the tasks given to the robots are changed. Based on object-oriented programming paradigm, we present useful software objects describing robot application programming environment. The object-oriented programming paradigm increases the software reusability, reliability, and extensibility, and also provides the structual concepts to cope with the various demands of robot application programming.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.164-169
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• 1998

Complex "lifelike" behaviors are composed of local interactions of individuals under fundamental rules of artificial life. In this paper, fundamental rules for cooperative group behaviors, "flocking" and "arrangement", of multiple autonomous mobile robots are represented by a small number of fuzzy rules. Fuzzy rules in Sugeno type and their related paramenters are automatically generated from clustering input-output data obtained from the algorithms the group behaviors. Simulations demonstrate the fuzzy rules successfully realize group intelligence of mobile robots.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.411-412
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• 2011