지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.6 No.6
- 발행연도
- 2011.11
- 수록면
- 806 - 816 (11page)
이용수
초록· 키워드
오류제보하기
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.
목차
Abstract
1. Introduction
2. Related Works
3. Particle Filter-Based Location Estimation
4. Particle Filter-Based Object Tracking
5. Swarm Robot-Based Invader-Enclosing Technique
6. Potential Field-Based Path Planning and Mobile Robot Navigation
7. Simulation
8. Conclusion
Acknowledgments
References
참고문헌 (28)
참고문헌 신청
H.Yamaguchi / 1999 / A Cooperative Hunting Behavior byMobile Robot Troops / International Journal ofRobotics Research 18(9):931~940
D. J. Park / 2003 / Toward Finding anUniversal Search Algorithm for Swarm Robots / Proceedings of 2003 IEEE/RSJ Int. Conference onIntelligent Robots and Systems :1945~1950
K. Sugawara / 1998 / Cooperative behavior of interacting robots / Artificial Life and Robotics 2(2):62~67
G. Welch / 2006 / An Introduction to the KalmanFilter / UNC-Chapel Hill
S. J. Julier / 1997 / A New Extension of theKalman Filter to Nonlinear Systems / Proceedingsof AeroSense: 11th Int. Symp. Aerospace/DefenseSensing, Simulation and Controls :182~193
D. J. Park / 2003 / Toward Finding anUniversal Search Algorithm for Swarm Robots / Proceedings of 2003 IEEE/RSJ Int. Conference onIntelligent Robots and Systems :1945~1950
K. Sugawara / 1998 / Cooperative behavior of interacting robots / Artificial Life and Robotics 2(2):62~67
G. Welch / 2006 / An Introduction to the KalmanFilter / UNC-Chapel Hill
S. J. Julier / 1997 / A New Extension of theKalman Filter to Nonlinear Systems / Proceedingsof AeroSense: 11th Int. Symp. Aerospace/DefenseSensing, Simulation and Controls :182~193
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UCI(KEPA) : I410-ECN-0101-2013-560-000843416