Estimation of Angular Acceleration By a Monocular Vision Sensor
0
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
Recently, monitoring of two-body ground vehicles carrying extremely hazardous materials has been considered as one of the most important national issues. This issue induces large cost in terms of national economy and social benefit. To monitor and counteract accidents promptly, an efficient methodology is required. For accident monitoring, GPS can be utilized in most cases. However, it is widely known that GPS cannot provide sufficient continuity in urban cannons and tunnels. To complement the weakness of GPS, this paper proposes an accident monitoring method based on a monocular vision sensor. The proposed method estimates angular acceleration from a sequence of image frames captured by a monocular vision sensor. The possibility of using angular acceleration is investigated to determine the occurrence of accidents such as jackknifing and rollover. By an experiment based on actual measurements, the feasibility of the proposed method is evaluated.
Abstract
Recently, monitoring of two-body ground vehicles carrying extremely hazardous materials has been considered as one of the most important national issues. This issue induces large cost in terms of national economy and social benefit. To monitor and counteract accidents promptly, an efficient methodology is required. For accident monitoring, GPS can be utilized in most cases. However, it is widely known that GPS cannot provide sufficient continuity in urban cannons and tunnels. To complement the weakness of GPS, this paper proposes an accident monitoring method based on a monocular vision sensor. The proposed method estimates angular acceleration from a sequence of image frames captured by a monocular vision sensor. The possibility of using angular acceleration is investigated to determine the occurrence of accidents such as jackknifing and rollover. By an experiment based on actual measurements, the feasibility of the proposed method is evaluated.
참고문헌 (14)
- Bradski, G., "Learning OpenCV", pp.370~404 (2008), O’Reilly Media, Inc.
- Brown, D. C., "Decentering distortion of lenses", Photometric Engineering, 32, pp.444~462 (1966)
- Fosbury, A. M., "Kalman Filtering for Relative Inertial Navigation of Uninhabited Air Vehicles", AIAA Guidance, Navigation, and Control Conference (2006), AIAA
- 이은성, "Relative Positioning of Vehicles Carrying Hazardous Materials Using Real-Time Kinematic GPS", Journal of Positioning, Navigation, and Timing, 2(1), pp.19~31 (2013), 한국위성항법시스템학회[DOI]
- S.-B. Kim, "Ground vehicle navigation in harsh urban conditions by integrating inertial navigation system, global positioning system, odometer and vision data", IET Radar, Sonar & Navigation, 5(8), pp.814~ (2011), Institution of Engineering and Technology (IET)[DOI]
- Lee, B. S., "Performance Evaluation of Accident Detection using Hazard Material Transport Vehicle HILS", 2013 KGS Conference (2013)
- Lee, J. Y., "Design of Adaptive Filtering Algorithm for Relative Navigation", Proceedings of the World Congress on Engineering and Computer Science, 2 (2013)
- Ligorio, G., "Extended Kalman Filter- Based Methods for Pose Estimation Using Visual, Inertial and Magnetic Sensors: Comparative Analysis and Performance Evaluation", Sensors, 13, pp.1919~1941 (2013)
- 임준후, "GPS와 단일영상을 활용한 차량 이동 변위 추정", 석사, 항공전자공학과, pp.2013
- Lim, J. H., "Estimation of Vehicle Trajectory in Urban Area by GPS and Vision Sensor", The 14th IAIN Congress 2012 (2012)
- Soloviev, A., "Integration of GPS and vision measurements for navigation in GPS challenged environments", Position Location and Navigation Symposium, pp.826~833 (2010), IEEE[DOI]
- R. Tsai, "A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses", IEEE Journal on Robotics and Automation, 3(4), pp.323~344 (1987), Institute of Electrical & Electronics Engineers (IEEE)[DOI]
- Anh Vu, "Real-Time Computer Vision", DGPS-Aided Inertial Navigation System for Lane-Level Vehicle Navigation, 2012, pp.13(2), 899~913[DOI]
- Wang, J., "Integration of GPS", INS, IAPRSSIS, pp.2008, 37(B1)[DOI]