• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.416-422
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• 2013

This paper suggests a hybrid path planning method of multi-robots, where a path deviation prevention for maintaining a specific formation is implemented by using repulsive function, $A^*$ algorithm and UKF (Unscented Kalman Filter). The repulsive function in potential field method is used to avoid collision among robots and obstacles. $A^*$ algorithm helps the robots to find optimal path. In addition, error estimation based on UKF guarantees small path deviation of each robot during navigation. The simulation results show that the swarm robots with designated formation successfully avoid obstacles and return to the assigned formation effectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.687-693
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• 2012

In this paper, we propose a optimal deployment method for cooperative exploration of swarm robots. The proposed method consists of two parts such as optimal deployment and path planning. The optimal area deployment is proposed by the K-mean Algorithm and Voronoi tessellation. The path planning is proposed by the potential field method and A* Algorithm. Finally, the numerical experiments demonstrate the effectiveness and feasibility of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1122-1131
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• 2012

This paper presents obstacle avoidance method for scout robot or industrial robot in unknown environment by using IR sensor and vision system. In the proposed method, robots share the information where the obstacles are located in real-time, thus the robots can choose the best path for obstacle avoidance. Using IR sensor and vision system, multiple robots efficiently evade the obstacles by the proposed cooperation method. No landmark is used at wall or floor in experiment environment. The obstacles don't have specific color or shape. To get the information of the obstacle, vision system extracts the obstacle coordinate by using an image labeling method. The information obtained by IR sensor is about the obstacle range and the locomotion direction to decide the optimal path for avoiding obstacle. The experiment was conducted in $7m{\times}7m$ indoor environment with two-wheeled mobile robots. It is shown that multiple robots efficiently move along the optimal path in cooperation with each other in the space where obstacles are located.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.328-332
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• 2023

The Army has presented eight game-changers for future warfare through 'Army Vision 2050,' including Intelligent Combat Robots, Super Soldiers, Energy Weapons, Hypersonic Weapons, Non-lethal Weapons, Autonomous Mobile Equipment, Intelligent Command and Control Systems, and Energy Supply Systems. This study focuses on Intelligent Combat Robots, considering them as the most crucial element among the mentioned innovations. How will Intelligent Combat Robots be utilized on the future battlefield? The future battlefield is expected to take the form of combined human-robot warfare, where advancements in science and technology allow intelligent robots to replace certain human roles. Especially, tasks known as Dirty, Difficult, Dangerous, and Dull (4D) in warfare are expected to be assigned to robots. This study suggests three forms of Intelligent Robots: humanoid robots, biomimetic robots, and swarm drones.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1886-1887
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• 2011

본 논문은 군집 로봇 포메이션 이동 제어를 위한 방법을 제안한다. Potential field method 알고리즘을 이용하여 Leader-Bot의 장애물 회피와 이동 경로를 계획한다. Leader-bot을 기준으로 하는 Follewer-bot의 포메이션 형성을 위해 Formation generated function을 사용한다. Leader-bot과 Follower-bot들 간에 충돌회피와 Follower-bot들의 장애물 회피를 위해 Potential function을 적용한다. 제안한 방법은 시뮬레이션을 통하여 실제 운용 가능성을 검증한다.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1890-1891
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• 2011

본 논문은 변형 가능한 타원형의 포메이션을 유지하기 위한 군집 로봇의 행동 동기화 알고리즘을 제안한다. 알고리즘은 매개 변수 함수를 이용한 타원형 포메이션에서의 포텐셜 필드 생성 부분과 개별 로봇이 타원으로 이동하기 위한 인력 및 충돌 회피를 위한 척력 함수 부분으로 나누어진다. 제안한 알고리즘은 시뮬레이션을 통해 군집 로봇의 행동을 제어하는데 효과적임을 입증하였다.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1837_1838
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• 2009

본 논문에서는 Particle Swarm Optimization(PSO)을 이용하여 지능형 로봇의 주행 제어 방법을 제안한다. 지능형 로봇의 주행을 위한 퍼지 제어기를 설계하고 퍼지 규칙을 구성하고 있는 멤버쉽 함수의 매개 변수를 PSO를 이용하여 동정한다. 최종 PSO로 동정된 매개변수를 이용하여 벽면 주행을 수행한다. 마지막으로, 실험을 통해 그 응용 가능성을 증명한다.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.60-72
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• 2016

This study proposes a multi-robot system, using multiple autonomous robots, to explore concrete structures and assist in their maintenance by sealing any cracks present in the structure. The proposed system employed a new self-localization method that is essential for autonomous robots, along with a visualization system to recognize the external environment and to detect and explore cracks efficiently. Moreover, more efficient crack search in an unknown environment became possible by arranging the robots into search areas divided depending on the surrounding situations. Operations with increased efficiency were also realized by overcoming the disadvantages of the infeasible logical behavioral model design with only six basic behavioral strategies based on distributed control-one of the methods to control swarm robots. Finally, this study investigated the efficiency of the proposed multi-robot system via basic sensor testing and simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.871-872
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• 2014

In this paper, I propose the method of cooperative work of swarm robot for escaping maze. The robots can communicate with each other using Zigbee, but the central control system send commands to robots because of low processing power of robots. Robots navigate the blinded maze and send information such as movement to the central control system for building map. The central control system analysis the received data and find path to escape from maze.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1441-1446
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• 2014

For the escape from a maze, the cooperative method by robot swarm was proposed in this paper. The robots can freely move by collecting essential data and making a decision in the use of sensors; however, a central control system is required to organize all robots for the escape from the maze. The robots explore new mazes and then send the information to the system for analyzing and mapping the escaping route. Three issues were considered as follows for the effective escape by multiple robots from the mazes in this paper. In the first, the mazes began to divide and secondly, dead-ends should be blocked. Finally, after the first arrivals at the destination, a shortcut should be provided for rapid escaping from the maze. The parallel-escape algorithms were applied to the different size of mazes, so that robot swarm can effectively get away the mazes.