• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.176-180
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• 1998

We may gaze at some peculiar scenes of flocking of birds and fishes. This paper demonstrates that multiple agent mobile robots show complex behaviors from efficient and strategic rules. The simulated flock are realized by a distributed behavioral model and each mobile robot decides its own motion as an individual which moves constantly by sensing the dynamic environment.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.519-522
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• 2005

This paper presents a self-organizing scheme for multi-agent swarm systems based on coupled nonlinear oscillators (CNOs). In this scheme, unicycle robots self-organize to flock and arrange group formation through attractive and repulsive forces among themselves. It is also shown how localized distributed controls are utilized throughout group behaviors such as formation and migration. In the paper, the proposed formation ensures safe separation and good cohesion performance among the robots. Several examples show that the proposed method for group formation performs the group behaviors such as reference path following, obstacle avoidance and flocking, and the formation characteristics such as flexibility and scalability, effectively.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.222-229
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• 2005

This paper presents a self-organizing scheme for multi-agent swarm systems based on coupled nonlinear oscillators (CNOs). In this scheme, unicycle robots self-organize to flock and arrange group formation through attractive and repulsive forces among themselves. The main result is the maintenance of flexible and scalable formation. It is also shown how localized distributed controls are utilized throughout group behaviors such as formation and migration. In the paper, the proposed formation ensures safe separation and good cohesion performance among the robots. Several examples show that the proposed method for group formation performs the group behaviors such as reference path following, obstacle avoidance and flocking, and the formation characteristics such as flexibility and scalability, effectively.

• Journal of Korea Game Society
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• v.9 no.2
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• pp.115-123
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• 2009

This paper proposes an algorithm to improve the performance of the spatial partitioning method for flocking behaviors. The core concept is to improve the performance by using the fact that even if a moving entity, boid in flock continuously changes its direction and position, its k-nearest neighbors, kNN to effect on decision of the next direction is not changed frequently. From the previous kNN, the method to check whether new kNN is changed or not is proposed in this paper and then the correctness of the proposed method is proved by two theorems. The proposed algorithm was implemented and its performance was compared with the conventional spatial partitioning method. The results of the comparison show that the proposed algorithm outperforms the conventional one by about 30% with respect to the number of frames per a second.

• Journal of Korea Game Society
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• v.11 no.1
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• pp.111-120
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• 2011

It is important to realistically simulate group behaviors of the multi-agents in virtual worlds. While most researchers have focused on their group behaviors in an open space, this paper studies their group behaviors by using steering force in an enclosed space. Agents have a common target and should move towards it in an enclosed space while avoiding collision with other agents. Under those environments, three possible models of agents are proposed and the six steering forces needed in each model are also proposed. In order to show the correctness of the proposed models, they were simulated. Our simulation results showed that the proposed models only using steering forces operate well in the enclosed space although it requires a different period of time for each agent to arrive at its target depending on the walls and doors.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.333-342
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• 2004

This paper presents a framework for the self-organization of swarm systems based on coupled nonlinear oscillators (CNOs). In this scheme, multiple agents in a swarm self-organize to flock and arrange themselves as a group using CNOs, which are able to keep a certain distance by the attractive and repulsive forces among different agents. A theoretical approach of flocking behavior by CNOs and a design guideline of CNO parameters are proposed. Finally, the formation scenario for cooperative multi-agent groups is investigated to demonstrate group behaviors such as aggregation, migration, homing and so on. The task for each group in this scenario is to perform a series of processes such as gathering into a whole group or splitting into two groups, and then to return to the base while avoiding collision with agents in different groups and maintaining the formation of each group.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.253-262
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• 2008

This paper presents a framework for decentralized control of self-organizing swarm systems based on the artificial potential functions (APFs). The framework explores the benefits by associating agents based on position information to realize complex swarming behaviors. A key development is the introduction of a set of association rules by APFs that effectively deal with a host of swarming issues such as flexible and agile formation. In this scheme, multiple agents in a swarm self-organize to flock and achieve formation control through attractive and repulsive forces among themselves using APFs. In particular, this paper presents an association rule for swarming that requires less movement for each agent and compact formation among agents. Extensive simulations are presented to illustrate the viability of the proposed framework.