Cooperative localization and multi-robot exploration
Cooperative localization and multi-robot exploration
Characterization and optimization of the accuracy of mobile robot localization
Characterization and optimization of the accuracy of mobile robot localization
An improved method for multi-robot cooperative localization based on relative bearing
ROBIO '09 Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics
Consistent cooperative localization
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
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In this paper, we present a new approach to the problem of simultaneous distributed localization for Multiple Autonomous Underwater Vehicles(MAUVs). Cooperative Localization (CL) is a crucial cycle for long range navigation of MAUVs. In the Leader-follower cooperative structure, a collective estimator is processed in the form of a extended Kalman filter. Different from the normal decentralized filter that only be decomposed of the collective filter, the distributed suboptimal method proposed in this paper is to reconstruct new measurements to the filter, so as to be decoupled from other sub-filters. Additionally, considering the data re-use problem in the proposed method, the improvement is also proposed. Finally, simulation results are tested to verify the advantage of the distributed suboptimal algorithm, and some comparisons are also provided.