• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.229-232
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• 2005

본 논문에서는 다수의 로봇이 협동 제어 및 분산 제어를 목적으로 고안된 DARS 로봇의 마이크로 컨트롤러가 적은 메모리를 내장하여 영상 처리와 같은 많은 데이터를 처리하는 부분에서는 여러 제약이 생기는 문제점을 해결하기 위하여 DARS 로봇의 영상 처리 및 전송에 있어 데이터의 전송량을 줄이는 방법으로 영상 압축 방식을 사용하여 영상 압축 데이터의 전송을 구현하였다. 또한 DARS 로봇이 이동하면서 특정 미션의 수행이 가능하도록 배터리로 정전압을 공급하고, 물체를 감지하는데 있어 사각이 없이 $360^{\circ}$전 방향을 감지하도록 적외선 센서부를 설계하였다. DARS 로봇의 이동이 용이하도록 설계된 모터 구동부는 센서에 감지되는 물체의 거리에 따라 DARS 로봇이 속도를 정밀하게 가$\cdot$감속 제어를 하고, 마이컴 제어부는 카메라로부터 입력되 영상 신호를 압축 알고리즘을 이용하여 압축하고, 압축된 데이터를 컴퓨터로 전송한다. 컴퓨터에서는 입력된 영상을 Visual c++을 사용하여 화면 표시 및 DARS 로봇을 제어 할 수 있도록 구현하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1044-1047
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• 2005

In this paper, we present the strategy of object search for distributed autonomous robotic systems (DARS). The DARS are the systems that consist of multiple autonomous robotic agents to whom required functions are distributed. For instance, the agents should recognize their surrounding at where they are located and generate some rules to act upon by themselves. In this paper, we introduce the strategy for multiple DARS robots to search a hidden object at the unknown area. First, we present an area-based action making process to determine the direction change of the robots during their maneuvers. Second, we also present Q learning adaptation to enhance the area-based action making process. Third, we introduce the coordinate system to represent a robot's current location. In the end of this paper, we show experimental results using hexagon-based Q learning to find the hidden object.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2346-2349
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• 2005

Distributed Autonomous Robotic System (DARS) is defined as a system that independent autonomous robots in the restricted environments infer their status from pre-assigned conditions and operate their jobs through the cooperation with each other. In the DARS, a robot contains sensor part to percept the situation around themselves, communication part to exchange information, and actuator part to do a work. Especially, in order to cooperate with other robots, communicating with other robots is one of the essential elements. Because Bluetooth has many advantages such as low power consumption, small size module package, and various standard protocols, Bluetooth is rated as one of the efficient communicating technologies which can apply to small-sized robot system. In this paper, we will develop Bluetooth communicating system for autonomous robots such as DARS robots. For this purpose, The Bluetooth communication system must have several features. The first, this system should be separated from other robot parts and operate spontaneously and independently. In other words, this communication system should have the ability to organize and maintain and reorganize a network scheme. The next, this system had better support any kinds of standard interfaces in order to guarantee flexible applicability to other embedded system. We will discuss how to construct and what kind of procedure to develop the network system.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.124-127
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• 1997

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 condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is simulated and suppressed by other robot using communication. Finally much simulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.297-300
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• 2004

Distributed Agent Robotic System (DARS)은 독립된 로봇 개체들이 스스로 판단하고 행동하는 시스템이다. DARS에서는 각 개체가 주위 환경과 이웃한 개체들의 상태를 인식하고 자신의 처한 환경에 맞게 행동해야 한다. 따라서 DARS 시스템에서는 센서와 같이 주위 환경을 인식하는 시스템이 매우 중요한 역할을 담당한다. 특히 주위의 장애물을 회피하거나 이웃한 개체와의 거리를 측정하기 위한 시스템은 DARS에서는 필수적이다. 물체와의 거리를 판별하기 위해서는 적외선이나 초음파를 이용한 시스템이 많이 사용된다. 본 논문에서는 적외선 센서를 이용한 거리 측정 시스템을 제안한다. 적외선을 쏘고 물체에 반사되어 나오는 적외선의 세기를 이용해서 거리를 측정할 수 있기 때문이다. 또한 DARS의 거리 측정 시에 고려해야 할 환경적인 요인에 대해 알아보고 실험을 통해서 미칠 수 있는 영향력을 측정한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.94-97
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• 2004

독립된 자율로봇에서 머신비젼의 구동을 위해 본 논문에서는 DARS(Distributed Autonomous Robotic System)에 적용하기 위한 디지털 이미지 프로세싱을 연구하고, DARS의 개별 로봇에 이를 임베디드화하는 것을 연구한다. 따라서 로봇을 구동하기 위해 필요한 데이터를 CMOS 카메라로부터 수신하여 영상을 스캔한 후, 원영상을 신경망 알고리즘을 통해 클러스터링하여 필요한 데이터를 추출한다. 또 이를 사용자 컴퓨터 단말기 상에 디스플레이하고, 최종적으로 DARS의 자율 이동 로봇이 영상 데이터를 인지하여 특정한 선택 동작을 수행하도록 한다.

• KIISE Transactions on Computing Practices
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• v.23 no.10
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• pp.588-593
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• 2017

In this paper, we propose a LiDAR driver that virtualizes multiple inexpensive LiDARs (Light Detection and Ranging) with a smaller number of scan channels on an autonomous vehicle to replace a single expensive LiDAR with a larger number of scan channels. As a result, existing SLAM (Simultaneous Localization And Mapping) algorithms can be used with no modifications developed assuming a single LiDAR. In the paper, the proposed driver was implemented on the Robot Operating System and was evaluated with an existing SLAM algorithm. The results show that the proposed driver, combined with a filter to control the density of points in a 3D map, is compatible with the existing algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1079-1085
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• 2000

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody, and control parameter as a T-cell, respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.627-633
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• 1999

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). Immune system is living body's self-protection and self-maintenance system. These features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For applying immune system to DARS, a robot is regarded as a ？3-cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robot using communication (immune network). Finally much stimulated strateby is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of optimal swarm strategy. Adaptation ability of robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• 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.