The authors proposed a moving long baseline algorithm based on the extended Kalman filter （EKF） for cooperative navigation and localization of multi-unmanned underwater vehicles （UUVs）. Research on cooperative nav...The authors proposed a moving long baseline algorithm based on the extended Kalman filter （EKF） for cooperative navigation and localization of multi-unmanned underwater vehicles （UUVs）. Research on cooperative navigation and localization for multi-UUVs is important to solve navigation problems that restrict long and deep excursions. The authors investigated improvements in navigation accuracy. In the moving long base line （MLBL） structure, the master UUV is equipped with a high precision navigation system as a node of the moving long baseline, and the slave UUV is equipped with a low precision navigation system. They are both equipped with acoustic devices to measure relative location. Using traditional triangulation methods to calculate the position of the slave UUV may cause a faulty solution. An EKF was designed to solve this, combining the proprioceptive and exteroceptive sensors. Research results proved that the navigational accuracy is improved significantly with the MLBL method based on EKF.展开更多
This paper deals with a cooperative control problem of a team of double-integrator agents moving along a set of given curves with a nominated formation. A projection-tracking design method is proposed for designing th...This paper deals with a cooperative control problem of a team of double-integrator agents moving along a set of given curves with a nominated formation. A projection-tracking design method is proposed for designing the path-following control and the formation protocol, which guarantee forma- tion motion of the multi-agent system under a directed communication graph. Necessary and sufficient conditions of the control gains for solving the coordinated problem are obtained when the directed communication graph has a globally reachable node. Simulation results of formation motion among three agents demonstrate the effectiveness of the proposed approach.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No.60875071the High Technology Research and Development Program of China under Grant No.2007AA0676the Program for New Century Excellent Talents in University under Grant No.NCET-06-0877
文摘The authors proposed a moving long baseline algorithm based on the extended Kalman filter （EKF） for cooperative navigation and localization of multi-unmanned underwater vehicles （UUVs）. Research on cooperative navigation and localization for multi-UUVs is important to solve navigation problems that restrict long and deep excursions. The authors investigated improvements in navigation accuracy. In the moving long base line （MLBL） structure, the master UUV is equipped with a high precision navigation system as a node of the moving long baseline, and the slave UUV is equipped with a low precision navigation system. They are both equipped with acoustic devices to measure relative location. Using traditional triangulation methods to calculate the position of the slave UUV may cause a faulty solution. An EKF was designed to solve this, combining the proprioceptive and exteroceptive sensors. Research results proved that the navigational accuracy is improved significantly with the MLBL method based on EKF.
基金supported by National Natural Science Foundation of China under Grant Nos.60974041 and 60934006
文摘This paper deals with a cooperative control problem of a team of double-integrator agents moving along a set of given curves with a nominated formation. A projection-tracking design method is proposed for designing the path-following control and the formation protocol, which guarantee forma- tion motion of the multi-agent system under a directed communication graph. Necessary and sufficient conditions of the control gains for solving the coordinated problem are obtained when the directed communication graph has a globally reachable node. Simulation results of formation motion among three agents demonstrate the effectiveness of the proposed approach.
