• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1292-1294
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• 2015

4족 보행 로봇이 환경에 동적으로 적응하여 자신에게 최적의 운동을 만들어 내는 연구는 중요하다. 우리는 유전알고리즘을 이용하여 전진 걸음새 동적 학습 시스템을 제안하였다. 이 시스템의 핵심은 로봇의 운동과 이 운동의 결과를 피드백해주는 센서들이다.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.720-725
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• 2004

Robot systems have applied to manufacturing or industrial field for reducing the need for human presence in dangerous and/or repetitive tasks. However, robot applications are transformed from industrial field to human life in recent tendency Nowadays, final goal of robot is to make a intelligent robot that can understand what human say and learn by itself and have internal emotion. For example Home service robots are able to provice functions such as security, housework, entertainment, education and secretary To provide various functions, home robots need to recognize human`s requirement and environment, and it is indispensable to use artificial intelligence technology for implementation of home robots. In this paper, implemented robot system takes data from several sensors and fuses the data to recognize environment information. Also, it can select a proper behavior for environment using soft computing method. Each behavior is composed with intuitive motion and sound in order to let human realize robot behavior well.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.800-803
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• 2020

실 환경 로봇에 강화학습을 적용하기 위해서는 가상 환경 시뮬레이션이 필요하다. 그러나 가상 환경을 구축하는 플랫폼은 모두 다르고, 학습 알고리즘의 구현에 따른 성능 편차가 크다는 문제점이 있다. 또한 학습을 적용하고자 하는 대상이 실세계의 하드웨어 사양이 낮은 스마트 로봇인 경우, 계산량이 많은 학습 알고리즘을 적용하기는 쉽지 않다. 본 연구는 해당 문제를 해결하기 위해 Unity3D에서 제공하는 강화학습 프레임인 ML-Agents 모듈을 사용하여 실 환경의 저사양 스마트 로봇에 장애물을 회피하고 탐색하는 모델의 강화학습을 적용해본다. 본 연구의 유의점은 가상 환경과 실 환경의 유사함과 일정량의 노이즈 발생 처리이다. 로봇의 간단한 행동은 원만하게 학습 및 적용가능함을 확인할 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.745-748
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• 2021

가상 환경의 시뮬레이션을 이용해 지능형 로봇에 강화 학습 기법을 적용하는 접근법은 실제 세계의 로봇들의 학습에 유용하다. 우리는 이러한 방법을 적용해서 장애물을 회피하고, 로봇이 특정 목표물을 인식하면 목표물로 자율적으로 이동하는 알고리즘을 개발하였다. 제안된 방법의 유용성 검증은 구현과 실험으로 확인하였다.

• ETRI Journal
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• v.44 no.2
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• pp.183-193
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• 2022

Smart cities are expected to provide residents with convenience via various agents such as CCTV, delivery robots, security robots, and unmanned shuttles. Environmental data collected by various agents can be used for various purposes, including advertising and security monitoring. This study suggests a surveillance map data framework for efficient and integrated multimodal data representation from multi-agents. The suggested surveillance map is a multilayered global information grid, which is integrated from the multimodal data of each agent. To confirm this, we collected surveillance map data for 4 months, and the behavior patterns of humans and vehicles, distribution changes of elevation, and temperature were analyzed. Moreover, we represent an anomaly detection algorithm based on a surveillance map for security service. A two-stage anomaly detection algorithm for unusual situations was developed. With this, abnormal situations such as unusual crowds and pedestrians, vehicle movement, unusual objects, and temperature change were detected. Because the surveillance map enables efficient and integrated processing of large multimodal data from a multi-agent, the suggested data framework can be used for various applications in the smart city.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.629-631
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• 2016

This paper dealt with the traveling robot for a robot to recognize a face.. This is to be carried out in a robotics basically. At the same time it can be described as utilizing available technology in various fields.In this paper, we envisioned that the operation of the face recognition biometric technology as a security measure in a particular space on the mobile robot.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.439-442
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• 2016

제한된 환경에서 로봇이 동적 장애물들에 대해 능동적으로 대처하며 목표한 지점까지 도달하기 위한 알고리즘을 제안한다. 로봇은 행동기반 시스템으로 만들어져 주변 장애물들을 자율적으로 회피한다. ex-agent는 공중에서 주변 환경들을 modeling 한 뒤 cell-map을 만들어 $A^*$알고리즘을 통해 이동 경로를 설정한다. 이동 경로와 로봇의 진행방향을 비교하여 회전 방향을 조언해준다. 로봇은 ex-agent 로부터 받은 조언과 센서값들을 조율하여 장애물들을 능동적으로 회피하며 목표 위치를 찾아갈 수 있다. 실험은 시뮬레이터를 통해 이루어졌으며 장애물들에 대해 원반한 회피율을 보였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.775-778
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• 2016

로봇 주행 기술은 전통적인 로봇요소 기술 외에도 여러 기술로 대상 응용서비스에 따라 IT 기술과 적극적인 융합을 통해 다양한 주행방법과 주행성능이 향상되고 있다. 본 논문에서는 대표적인 실내 모바일 로봇인 로봇 청소기를 대상으로 기존의 방법인 적외선과 카메라 방법이 아닌 보통 가정에도 쉽게 존재하는 AP를 이용해 목표를 설정하여 포섭구조 이론을 기반으로 동적인 환경에서도 충전 스테이션 까지 자율 주행이 가능한 로봇 알고리즘을 설계하였다. 그 결과 동적인 환경을 설정하여 로봇이 AP를 찾아가는 것을 확인하였고 주행 경로와 경과 시간을 표로 도출하여 다른 경우를 예측할 수 있게 하였다. 향후 행동 기반 로봇과 다양한 센서를 이용하여 로봇의 위치와 목표점 사이의 최단거리 경로를 구하여 주행하는 것이 목표이다.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.2
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• pp.204-210
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• 2018

As the 4th industrial revolution and artificial intelligence technology develop, it is expected that there will be a revolutionary changes in the security robot. However, artificial intelligence system requires enormous hardwares for tremendous computing loads, and there are many challenges that need to be addressed more technologically. This paper introduces precise tracking control technique of autonomous system that need to move repetitive paths for security purpose. The input feedforward signal is generated by using the inverse based iterative learning control theory for the 2 input 2 output nonminimum-phase system which was difficult to overcome by the conventional feedback control system. The simulation results of the input signal generation and precision tracking of given path corresponding to the repetition rate of extreme, such as bandwidth of the system, shows the efficacy of suggested techniques and possibility to be used in military security purposes.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.806-816
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• 2011

Interest about social security has recently increased in favor of safety for infrastructure. In addition, advances in computer vision and pattern recognition research are leading to video-based surveillance systems with improved scene analysis capabilities. However, such video surveillance systems, which are controlled by human operators, cannot actively cope with dynamic and anomalous events, such as having an invader in the corporate, commercial, or public sectors. For this reason, intelligent surveillance systems are increasingly needed to provide active social security services. In this study, we propose a core technique for intelligent surveillance system that is based on swarm robot technology. We present techniques for invader enclosing using swarm robots based on multiple distributed object environment. The proposed methods are composed of three main stages: location estimation of the object, specified object tracking, and decision of the cooperative behavior of the swarm robots. By using particle filter, object tracking and location estimation procedures are performed and a specified enclosing point for the swarm robots is located on the interactive positions in their coordinate system. Furthermore, the cooperative behaviors of the swarm robots are determined via the result of path navigation based on the combination of potential field and wall-following methods. The results of each stage are combined into the swarm robot-based invader-enclosing technique on multiple distributed object environments. Finally, several simulation results are provided to further discuss and verify the accuracy and effectiveness of the proposed techniques.