• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1884-1885
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• 2011

In the wireless sensor network (WSN) environment, the approximate point-in-triangulation (APIT) is a kind of range-free localization algorithm. This algorithm provides high precision, however, the coverage rate is somewhat poor. In this paper, we propose an improved APIT algorithm for the localization of swarm robots, which is based on the received signal strength indicator (RSSI) and the center of gravity (COG) methods.

• 한국지능시스템학회논문지
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• 제22권4호
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• pp.476-480
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• 2012

본 논문에서는 선도 로봇을 추종하는 군집 로봇의 대형 제어를 인공 포텐셜 장을 사용하여 제안한다. 또한, 인공 포텐셜 장은 물리적으로 해석하기 쉬운 전기장을 모델링하여 구성하고, 장애물을 더욱 효과적으로 모델링하기 위해서, 장애물의 모양에 따라 전기장의식을 달리한다. 제안하는 방법은 선도 로봇의 경로를 인공 포텐셜 장을 통해 계획한 뒤, 선도 로봇을 추종 로봇이 뒤따라가는 형태로 구성된다. 마지막으로 시뮬레이션 예제를 통해 제안하는 기법의 타당성을 검증한다.

• 제어로봇시스템학회논문지
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• 제13권2호
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• pp.163-172
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• 2007

A swarm-bot docking with two independent robots aiming at overcoming obstacles or climbing up/down stairs is introduced how it can be manufactured and controlled. Utilizing the fast mobility of the vehicle robot and cooperating between robots expands the applications of the robot. An algorithm for identifying the partner robot and its generic mechanism enabling the docking of two robots are addressed. The designed swarm-bot has advantages in terms of overcoming obstacle or stair climbing which is not easily implemented by a single robot, increasing the adaptability to the environment.

• 제어로봇시스템학회논문지
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• 제16권3호
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• pp.227-232
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• 2010

In this paper we consider the multi-robot system that collects target objects spread in an unexplored environment. The robots cooperate each other to improve the capability and the efficiency. The robots attract or intimidate each other as behaviors of bacterial swarms or particles with electrical moments. The interactions would increase the working efficiency in some environments but it would decrease the efficiency in some other environments. Therefore, the system needs to adapt to the working environment by adjusting the strengths of the interactions. The strengths of the interactions are expressed as sets of gene codes that mean the weights of each kind of attracting or intimidating vectors. The proposed system adjusts the gene codes using evolutional strategy. The proposed approach has been validated by computer simulation. The results of this paper show that our inter-swarm interacting strategy and optimizing algorithm improves the working efficiency, adaptively to the characteristics of environments.

• 드라이브 ㆍ 컨트롤
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• 제15권3호
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• pp.1-7
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• 2018

Humanoid robots have fascinated many researchers since they appeared decades ago. For the requirement of both accurate tracking control and the safety of physical human-robot interaction, torque control is basically desirable for humanoid robots. Humanoid robots are highly nonlinear, coupled, complex systems, accordingly the calculation of robot model is difficult and even impossible if precise model of the humanoid robots are unknown. Therefore, it is difficult to control using traditional model-based techniques. To realize model-free torque control, time-delay control (TDC) for humanoid robot was proposed with time-delay estimation technique. Using optimal walking trajectory obtained by particle swarm optimization, TDC with proposed scheme is implemented on whole body of a humanoid, not on biped legs even though it is performed by a virtual humanoid robot. The simulation results show the validity of the proposed TDC for humanoid robots.

• 한국생산제조학회지
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• 제25권6호
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• pp.504-510
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• 2016

Robots are widely utilized in many fields, and various demands need customized robots. This study proposes an optimal design method based on swarm intelligence for selecting the kinematic parameter of a manipulator according to the task space trajectory desired by the user. The optimal design method is dealt with herein as an optimization problem. This study is based on swarm intelligence-based optimization algorithms (i.e., ant colony optimization (ACO) and particle swarm optimization algorithms) to determine the optimal kinematic parameters of the manipulator. The former is used to select the optimal kinematic parameter values, whereas the latter is utilized to solve the inverse kinematic problem when the ACO determines the parameter values. This study solves a design problem with the PUMA 560 when the desired task space trajectory is given and discusses its results in the simulation part to verify the performance of the proposed design.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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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.

• 한국정밀공학회지
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• 제31권11호
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• pp.1023-1030
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• 2014

This paper presents a new method to control swarm robots so that they can keep the formation while following a curved path. The main idea is to utilize the information on the instant center of gyration. For a given path, location of the instant center of the formation center is calculated, and individual robots follow the circular path around the calculated instant center. Performance of curvature-radius based method is compared with leader-follower referenced method via MATLAB simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권3호
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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.

• 한국지능시스템학회논문지
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• 제22권6호
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• pp.687-693
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• 2012

본 논문에서는 군집로봇의 효과적인 협조탐색을 위한 탐색영역에 대한 군집로봇의 최적배치을 제안한다. 먼저, 탐색영역에 대한 최적의 배치를 위해 보로노이 테셀레이션과 K-mean 알고리즘을 이용하여 탐색영역을 분할한다. 분할된 영역을 안전한 주행을 위해 전역경로계획과 지역경로계획을 한다. 전역경로계획은 A*알고리즘을 이용하여 전역경로계획을 하여 최적의 전역경로를 찾고, 지역경로계획은 포텐셜 필드방법을 이용하여 장애물 회피 통해 안전하게 목표점에 이르게 한다. 마지막으로 제안한 알고리즘은 시물레이션을 통해 그 응용가능성을 검토한다.