A unified approach of observability analysis for airborne SLAM
来源期刊：中南大学学报(英文版)2013年第9期
论文作者：FANG Qiang(方强) HUANG Xin-sheng(黄新生)
文章页码：2432 - 2439
Key words：unmanned aerial vehicle (UAV); simultaneous localization and mapping (SLAM); inertial navigation system (INS); observability; extend Kalman filter (EKF)
Abstract: An unmanned aerial vehicle (UAV) is arranged to explore an unknown environment and to map the features it finds when GPS is denied. It navigates using a statistical estimation technique known as simultaneous localization and mapping (SLAM) which allows for the simultaneous estimation of the location of the UAV as well as the location of the features it sees. Observability is a key aspect of the state estimation problem of SLAM. However, the dimension and variables of SLAM system might be changed with new features. To solve this issue, a unified approach of observability analysis for SLAM system is provided, through reorganizing the system model. The dimension and variables of SLAM system keep steady, then the PWCS theory can be used to analyze the local or total observability, and under special maneuver, some system states, such as the yaw angle, become observable. Simulation results validate the proposed method.
FANG Qiang(方强), HUANG Xin-sheng(黄新生)
(College of Mechatronics Engineering and Automation, National University of Defense Technology,
Changsha 410073, China)
Abstract:An unmanned aerial vehicle (UAV) is arranged to explore an unknown environment and to map the features it finds when GPS is denied. It navigates using a statistical estimation technique known as simultaneous localization and mapping (SLAM) which allows for the simultaneous estimation of the location of the UAV as well as the location of the features it sees. Observability is a key aspect of the state estimation problem of SLAM. However, the dimension and variables of SLAM system might be changed with new features. To solve this issue, a unified approach of observability analysis for SLAM system is provided, through reorganizing the system model. The dimension and variables of SLAM system keep steady, then the PWCS theory can be used to analyze the local or total observability, and under special maneuver, some system states, such as the yaw angle, become observable. Simulation results validate the proposed method.
Key words:unmanned aerial vehicle (UAV); simultaneous localization and mapping (SLAM); inertial navigation system (INS); observability; extend Kalman filter (EKF)
