GPS and Odometry Information based Outdoor Localization- Research Background
- GPS data filtering using its deviation data
- Using weighted GPS data in Kalman filter by analyzing information in real-time
Fig. 1 Experimental environment
- Research Objectives
- Stable localization using extended Kalman filter by fusing GPS data and odometry information
Fig. 2 Localization result : (a) deviation of GPS position data according to the environments, (b) case 1 : localization result with conventional EKF, (c) localization result with using proposed method
Fig. 3 Comparison between conventional purpose and proposed purpose : left : A of the environment, right : B of the environment
- Paper 1 :
배지훈, 송재복, 최지훈, 가중화된 GPS 정보와 지도정보를 활용한 실외 이동로봇의 위치추정 (Outdoor Localization of a Mobile Robot Using Weighted GPS Data and Map Information), 로봇학회 논문지, Vol. 6, No. 3, pp. 292-300, 2011.09.
* Last updated: 2012. 4. 30 |
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